diff --git a/configure.ac b/configure.ac
index bbfdd490ac8516f67cfd2fdb320263d1bd336671..2ce845cd9130bed37e250bd83000cb5a6762b7fc 100644
--- a/configure.ac
+++ b/configure.ac
@@ -82,10 +82,6 @@ CPPFLAGS="$CPPFLAGS_SAVED"
# Don't use deprecated hash structures
AC_DEFINE([BOOST_NO_HASH], [], [Don't use deprecated STL hash structures])
-# Check for dlopen(), needed by tests for estimation DLL
-AC_CHECK_LIB([dl], [dlopen], [LIBADD_DLOPEN="-ldl"], [])
-AC_SUBST([LIBADD_DLOPEN])
-
AC_CHECK_PROG([MAKEINFO], [makeinfo], [makeinfo])
AC_CHECK_PROG([PDFTEX], [pdftex], [pdftex])
@@ -203,10 +199,6 @@ AC_CONFIG_FILES([Makefile
dynare++/kord/Makefile
dynare++/src/Makefile
mex/sources/Makefile
- mex/sources/estimation/Makefile
- mex/sources/estimation/tests/Makefile
- mex/sources/estimation/libmat/Makefile
- mex/sources/estimation/libmat/tests/Makefile
])
AC_ARG_ENABLE([matlab], AS_HELP_STRING([--disable-matlab], [disable compilation of MEX files for MATLAB]), [], [enable_matlab=yes])
diff --git a/mex/build/estimation.am b/mex/build/estimation.am
deleted file mode 100644
index b2a92a32680fb9d82cb744b82f9f0eb4624ffba2..0000000000000000000000000000000000000000
--- a/mex/build/estimation.am
+++ /dev/null
@@ -1,67 +0,0 @@
-noinst_PROGRAMS = logposterior logMHMCMCposterior
-
-# We use shared flags so that automake does not compile things two times
-CPPFLAGS += -I$(top_srcdir)/../../sources/estimation/libmat -I$(top_srcdir)/../../sources/estimation/utils $(BOOST_CPPFLAGS)
-LDFLAGS += $(BOOST_LDFLAGS)
-LDADD = $(LIBADD_DLOPEN)
-
-TOPDIR = $(top_srcdir)/../../sources/estimation
-
-MAT_SRCS = \
- $(TOPDIR)/libmat/Matrix.hh \
- $(TOPDIR)/libmat/Matrix.cc \
- $(TOPDIR)/libmat/Vector.hh \
- $(TOPDIR)/libmat/Vector.cc \
- $(TOPDIR)/libmat/BlasBindings.hh \
- $(TOPDIR)/libmat/DiscLyapFast.hh \
- $(TOPDIR)/libmat/GeneralizedSchurDecomposition.cc \
- $(TOPDIR)/libmat/GeneralizedSchurDecomposition.hh \
- $(TOPDIR)/libmat/LapackBindings.hh \
- $(TOPDIR)/libmat/LUSolver.cc \
- $(TOPDIR)/libmat/LUSolver.hh \
- $(TOPDIR)/libmat/QRDecomposition.cc \
- $(TOPDIR)/libmat/QRDecomposition.hh \
- $(TOPDIR)/libmat/VDVEigDecomposition.cc \
- $(TOPDIR)/libmat/VDVEigDecomposition.hh
-
-COMMON_SRCS = \
- $(MAT_SRCS) \
- $(TOPDIR)/DecisionRules.cc \
- $(TOPDIR)/DecisionRules.hh \
- $(TOPDIR)/DetrendData.cc \
- $(TOPDIR)/DetrendData.hh \
- $(TOPDIR)/EstimatedParameter.cc \
- $(TOPDIR)/EstimatedParameter.hh \
- $(TOPDIR)/EstimatedParametersDescription.cc \
- $(TOPDIR)/EstimatedParametersDescription.hh \
- $(TOPDIR)/EstimationSubsample.cc \
- $(TOPDIR)/EstimationSubsample.hh \
- $(TOPDIR)/InitializeKalmanFilter.cc \
- $(TOPDIR)/InitializeKalmanFilter.hh \
- $(TOPDIR)/KalmanFilter.cc \
- $(TOPDIR)/KalmanFilter.hh \
- $(TOPDIR)/LogLikelihoodSubSample.cc \
- $(TOPDIR)/LogLikelihoodSubSample.hh \
- $(TOPDIR)/LogLikelihoodMain.hh \
- $(TOPDIR)/LogLikelihoodMain.cc \
- $(TOPDIR)/LogPosteriorDensity.cc \
- $(TOPDIR)/LogPosteriorDensity.hh \
- $(TOPDIR)/LogPriorDensity.cc \
- $(TOPDIR)/LogPriorDensity.hh \
- $(TOPDIR)/ModelSolution.cc \
- $(TOPDIR)/ModelSolution.hh \
- $(TOPDIR)/Prior.cc \
- $(TOPDIR)/Prior.hh \
- $(TOPDIR)/utils/dynamic_dll.cc \
- $(TOPDIR)/utils/dynamic_dll.hh
-
-nodist_logposterior_SOURCES = \
- $(COMMON_SRCS) \
- $(TOPDIR)/logposterior.cc
-
-nodist_logMHMCMCposterior_SOURCES = \
- $(COMMON_SRCS) \
- $(TOPDIR)/Proposal.cc \
- $(TOPDIR)/Proposal.hh \
- $(TOPDIR)/RandomWalkMetropolisHastings.hh \
- $(TOPDIR)/logMHMCMCposterior.cc
diff --git a/mex/build/matlab/Makefile.am b/mex/build/matlab/Makefile.am
index 82904454fa45a094238b50ae3ace743a87563705..bfeaac393fa91f8f72eecfecf01a03ef1fe70b04 100644
--- a/mex/build/matlab/Makefile.am
+++ b/mex/build/matlab/Makefile.am
@@ -2,7 +2,7 @@ ACLOCAL_AMFLAGS = -I ../../../m4
# libdynare++ must come before gensylv, k_order_perturbation, dynare_simul_
if DO_SOMETHING
-SUBDIRS = mjdgges kronecker bytecode libdynare++ gensylv k_order_perturbation dynare_simul_ estimation block_kalman_filter sobol local_state_space_iterations
+SUBDIRS = mjdgges kronecker bytecode libdynare++ gensylv k_order_perturbation dynare_simul_ block_kalman_filter sobol local_state_space_iterations
if HAVE_GSL
SUBDIRS += ms_sbvar
diff --git a/mex/build/matlab/configure.ac b/mex/build/matlab/configure.ac
index 08be799c48940d0e217fc91276519e15300f3755..a393e04a3e06e0a4212ee7734368a8d19cec6164 100644
--- a/mex/build/matlab/configure.ac
+++ b/mex/build/matlab/configure.ac
@@ -139,7 +139,6 @@ AC_CONFIG_FILES([Makefile
gensylv/Makefile
k_order_perturbation/Makefile
dynare_simul_/Makefile
- estimation/Makefile
libslicot/Makefile
kalman_steady_state/Makefile
ms_sbvar/Makefile
diff --git a/mex/build/matlab/estimation/Makefile.am b/mex/build/matlab/estimation/Makefile.am
deleted file mode 100644
index 44c75b50f0436f645401c7c9798390624024b635..0000000000000000000000000000000000000000
--- a/mex/build/matlab/estimation/Makefile.am
+++ /dev/null
@@ -1,2 +0,0 @@
-include ../mex.am
-include ../../estimation.am
diff --git a/mex/build/octave/Makefile.am b/mex/build/octave/Makefile.am
index 132ddbe15889f4c84ed13e1e636454fdd66da581..9e29dd916681af42b9c3211d3bdb0e9fa306f0ec 100644
--- a/mex/build/octave/Makefile.am
+++ b/mex/build/octave/Makefile.am
@@ -15,7 +15,4 @@ if HAVE_FORT
SUBDIRS += libslicot kalman_steady_state
endif
-if HAVE_MATIO
-SUBDIRS += estimation
-endif
endif
diff --git a/mex/build/octave/configure.ac b/mex/build/octave/configure.ac
index c8aa1efe8f4d2335bea08287b659fe26073bba1e..3e2362005201e1137b541a7551acd01b092d637e 100644
--- a/mex/build/octave/configure.ac
+++ b/mex/build/octave/configure.ac
@@ -124,7 +124,6 @@ AC_CONFIG_FILES([Makefile
gensylv/Makefile
k_order_perturbation/Makefile
dynare_simul_/Makefile
- estimation/Makefile
qzcomplex/Makefile
ordschur/Makefile
libslicot/Makefile
diff --git a/mex/build/octave/estimation/Makefile.am b/mex/build/octave/estimation/Makefile.am
deleted file mode 100644
index bc9c58ab0e05a29b58c4b87f887612c7a249601e..0000000000000000000000000000000000000000
--- a/mex/build/octave/estimation/Makefile.am
+++ /dev/null
@@ -1,5 +0,0 @@
-EXEEXT = .mex
-include ../mex.am
-include ../../estimation.am
-
-logMHMCMCposterior_LDADD = $(LIBADD_MATIO)
diff --git a/mex/sources/Makefile.am b/mex/sources/Makefile.am
index 41b94ffa67d9bd6a879dbca859f322daabaacc53..ea08a0115608b4bf6b9beccc1f67668959e2dc50 100644
--- a/mex/sources/Makefile.am
+++ b/mex/sources/Makefile.am
@@ -1,5 +1,3 @@
-SUBDIRS = estimation
-
EXTRA_DIST = \
dynblas.h \
dynlapack.h \
diff --git a/mex/sources/estimation/DecisionRules.cc b/mex/sources/estimation/DecisionRules.cc
deleted file mode 100644
index f614f6090cce3f173ad331664fb1edb1508dd171..0000000000000000000000000000000000000000
--- a/mex/sources/estimation/DecisionRules.cc
+++ /dev/null
@@ -1,210 +0,0 @@
-/*
- * Copyright (C) 2010-2011 Dynare Team
- *
- * This file is part of Dynare.
- *
- * Dynare is free software: you can redistribute it and/or modify
- * it under the terms of the GNU General Public License as published by
- * the Free Software Foundation, either version 3 of the License, or
- * (at your option) any later version.
- *
- * Dynare is distributed in the hope that it will be useful,
- * but WITHOUT ANY WARRANTY; without even the implied warranty of
- * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
- * GNU General Public License for more details.
- *
- * You should have received a copy of the GNU General Public License
- * along with Dynare. If not, see <http://www.gnu.org/licenses/>.
- */
-
-#include <cassert>
-
-#include <algorithm>
-
-#include "DecisionRules.hh"
-
-DecisionRules::DecisionRules(size_t n_arg, size_t p_arg,
- const std::vector<size_t> &zeta_fwrd_arg,
- const std::vector<size_t> &zeta_back_arg,
- const std::vector<size_t> &zeta_mixed_arg,
- const std::vector<size_t> &zeta_static_arg,
- double qz_criterium) :
- n(n_arg), p(p_arg), zeta_fwrd(zeta_fwrd_arg), zeta_back(zeta_back_arg),
- zeta_mixed(zeta_mixed_arg), zeta_static(zeta_static_arg),
- n_fwrd(zeta_fwrd.size()), n_back(zeta_back.size()),
- n_mixed(zeta_mixed.size()), n_static(zeta_static.size()),
- n_back_mixed(n_back+n_mixed), n_fwrd_mixed(n_fwrd+n_mixed),
- n_dynamic(n-n_static),
- S(n, n_static),
- A(n, n_back_mixed + n + n_fwrd_mixed),
- D(n_fwrd + n_back + 2*n_mixed),
- E(n_fwrd + n_back + 2*n_mixed),
- Z_prime(n_fwrd + n_back + 2*n_mixed),
- QR(n, n_static, n_back_mixed + n + n_fwrd_mixed),
- GSD(n_fwrd + n_back + 2*n_mixed, qz_criterium),
- LU1(n_fwrd_mixed),
- LU2(n_back_mixed),
- LU3(n_static),
- Z21(n_fwrd_mixed, n_back_mixed),
- g_y_back(n_back_mixed),
- g_y_back_tmp(n_back_mixed),
- g_y_static(n_static, n_back_mixed),
- A0s(n_static),
- A0d(n_static, n_dynamic),
- g_y_dynamic(n_dynamic, n_back_mixed),
- g_y_static_tmp(n_fwrd_mixed, n_back_mixed),
- g_u_tmp1(n, n_back_mixed),
- g_u_tmp2(n),
- LU4(n)
-{
- assert(n == n_back + n_fwrd + n_mixed + n_static);
-
- set_union(zeta_fwrd.begin(), zeta_fwrd.end(),
- zeta_mixed.begin(), zeta_mixed.end(),
- back_inserter(zeta_fwrd_mixed));
- set_union(zeta_back.begin(), zeta_back.end(),
- zeta_mixed.begin(), zeta_mixed.end(),
- back_inserter(zeta_back_mixed));
- set_union(zeta_back_mixed.begin(), zeta_back_mixed.end(),
- zeta_fwrd.begin(), zeta_fwrd.end(),
- back_inserter(zeta_dynamic));
-
- // Compute beta_back and pi_back
- for (size_t i = 0; i < n_back_mixed; i++)
- if (find(zeta_mixed.begin(), zeta_mixed.end(), zeta_back_mixed[i])
- == zeta_mixed.end())
- pi_back.push_back(i);
- else
- beta_back.push_back(i);
-
- // Compute beta_fwrd and pi_fwrd
- for (size_t i = 0; i < n_fwrd_mixed; i++)
- if (find(zeta_mixed.begin(), zeta_mixed.end(), zeta_fwrd_mixed[i])
- == zeta_mixed.end())
- pi_fwrd.push_back(i);
- else
- beta_fwrd.push_back(i);
-}
-
-void
-DecisionRules::compute(const Matrix &jacobian, Matrix &g_y, Matrix &g_u) throw (BlanchardKahnException, GeneralizedSchurDecomposition::GSDException)
-{
- assert(jacobian.getRows() == n
- && jacobian.getCols() == (n_back_mixed + n + n_fwrd_mixed + p));
- assert(g_y.getRows() == n && g_y.getCols() == n_back_mixed);
- assert(g_u.getRows() == n && g_u.getCols() == p);
-
- // Construct S, perform QR decomposition and get A = Q*jacobian
- for (size_t i = 0; i < n_static; i++)
- mat::col_copy(jacobian, n_back_mixed+zeta_static[i], S, i);
-
- A = MatrixConstView(jacobian, 0, 0, n, n_back_mixed + n + n_fwrd_mixed);
- QR.computeAndLeftMultByQ(S, "T", A);
-
- // Construct matrix D
- D.setAll(0.0);
- for (size_t i = 0; i < n_mixed; i++)
- D(n - n_static + i, beta_back[i]) = 1.0;
- for (size_t j = 0; j < n_back_mixed; j++)
- mat::col_copy(A, n_back_mixed + zeta_back_mixed[j], n_static, n - n_static,
- D, j, 0);
- MatrixView(D, 0, n_back_mixed, n - n_static, n_fwrd_mixed) = MatrixView(A, n_static, n_back_mixed + n, n - n_static, n_fwrd_mixed);
-
- // Construct matrix E
- E.setAll(0.0);
- for (size_t i = 0; i < n_mixed; i++)
- E(n - n_static + i, n_back_mixed + beta_fwrd[i]) = 1.0;
- MatrixView(E, 0, 0, n - n_static, n_back_mixed) = MatrixView(A, n_static, 0, n - n_static, n_back_mixed);
- for (size_t j = 0; j < n_fwrd; j++)
- mat::col_copy(A, n_back_mixed + zeta_fwrd_mixed[pi_fwrd[j]], n_static, n - n_static,
- E, n_back_mixed + pi_fwrd[j], 0);
- MatrixView E_tmp(E, 0, 0, n - n_static, n_fwrd + n_back + 2*n_mixed);
- mat::negate(E_tmp); // Here we take the opposite of some of the zeros initialized in the constructor, but it is not a problem
-
- // Perform the generalized Schur
- size_t sdim;
- GSD.compute(E, D, Z_prime, sdim);
-
- if (n_back_mixed != sdim)
- throw BlanchardKahnException(true, n_fwrd_mixed, n_fwrd + n_back + 2*n_mixed - sdim);
-
- // Compute DR for forward variables w.r. to endogenous
- MatrixView Z21_prime(Z_prime, 0, n_back_mixed, n_back_mixed, n_fwrd_mixed),
- Z22_prime(Z_prime, n_back_mixed, n_back_mixed, n_fwrd_mixed, n_fwrd_mixed);
-
- mat::transpose(Z21, Z21_prime);
-
- try
- {
- LU1.invMult("T", Z22_prime, Z21);
- }
- catch (LUSolver::LUException &e)
- {
- throw BlanchardKahnException(false, n_fwrd_mixed, n_fwrd + n_back + 2*n_mixed - sdim);
- }
- mat::negate(Z21);
- const Matrix &g_y_fwrd = Z21;
-
- for (size_t i = 0; i < n_fwrd_mixed; i++)
- mat::row_copy(g_y_fwrd, i, g_y, zeta_fwrd_mixed[i]);
-
- // Compute DR for backward variables w.r. to endogenous
- MatrixView Z11_prime(Z_prime, 0, 0, n_back_mixed, n_back_mixed),
- T11(D, 0, 0, n_back_mixed, n_back_mixed),
- S11(E, 0, 0, n_back_mixed, n_back_mixed);
- mat::set_identity(g_y_back);
- g_y_back_tmp = Z11_prime;
- LU2.invMult("N", g_y_back_tmp, g_y_back);
- g_y_back_tmp = g_y_back;
- blas::gemm("N", "N", 1.0, S11, g_y_back_tmp, 0.0, g_y_back);
- LU2.invMult("N", T11, g_y_back);
- g_y_back_tmp = g_y_back;
- blas::gemm("N", "N", 1.0, Z11_prime, g_y_back_tmp, 0.0, g_y_back);
-
- // TODO: avoid to copy mixed variables again, rather test it...
- for (size_t i = 0; i < n_back_mixed; i++)
- mat::row_copy(g_y_back, i, g_y, zeta_back_mixed[i]);
-
- // Compute DR for static variables w.r. to endogenous
- g_y_static = MatrixView(A, 0, 0, n_static, n_back_mixed);
- for (size_t i = 0; i < n_dynamic; i++)
- {
- mat::row_copy(g_y, zeta_dynamic[i], g_y_dynamic, i);
- mat::col_copy(A, n_back_mixed + zeta_dynamic[i], 0, n_static, A0d, i, 0);
- }
- blas::gemm("N", "N", 1.0, A0d, g_y_dynamic, 1.0, g_y_static);
- blas::gemm("N", "N", 1.0, g_y_fwrd, g_y_back, 0.0, g_y_static_tmp);
- blas::gemm("N", "N", 1.0, MatrixView(A, 0, n_back_mixed + n, n_static, n_fwrd_mixed),
- g_y_static_tmp, 1.0, g_y_static);
- for (size_t i = 0; i < n_static; i++)
- mat::col_copy(A, n_back_mixed + zeta_static[i], 0, n_static, A0s, i, 0);
- LU3.invMult("N", A0s, g_y_static);
- mat::negate(g_y_static);
-
- for (size_t i = 0; i < n_static; i++)
- mat::row_copy(g_y_static, i, g_y, zeta_static[i]);
-
- // Compute DR for all endogenous w.r. to shocks
- blas::gemm("N", "N", 1.0, MatrixConstView(jacobian, 0, n_back_mixed + n, n, n_fwrd_mixed), g_y_fwrd, 0.0, g_u_tmp1);
- g_u_tmp2 = MatrixConstView(jacobian, 0, n_back_mixed, n, n);
- for (size_t i = 0; i < n_back_mixed; i++)
- {
- VectorView c1 = mat::get_col(g_u_tmp2, zeta_back_mixed[i]),
- c2 = mat::get_col(g_u_tmp1, i);
- vec::add(c1, c2);
- }
- g_u = MatrixConstView(jacobian, 0, n_back_mixed + n + n_fwrd_mixed, n, p);
- LU4.invMult("N", g_u_tmp2, g_u);
- mat::negate(g_u);
-}
-
-std::ostream &
-operator<<(std::ostream &out, const DecisionRules::BlanchardKahnException &e)
-{
- if (e.order)
- out << "The Blanchard-Kahn order condition is not satisfied: you have " << e.n_fwrd_vars << " forward variables for " << e.n_explosive_eigenvals << " explosive eigenvalues";
- else
- out << "The Blanchard Kahn rank condition is not satisfied";
- return out;
-}
-
diff --git a/mex/sources/estimation/DecisionRules.hh b/mex/sources/estimation/DecisionRules.hh
deleted file mode 100644
index 22e30bdf11967609f930fc0da3f0c60d13ca84cc..0000000000000000000000000000000000000000
--- a/mex/sources/estimation/DecisionRules.hh
+++ /dev/null
@@ -1,77 +0,0 @@
-/*
- * Copyright (C) 2010 Dynare Team
- *
- * This file is part of Dynare.
- *
- * Dynare is free software: you can redistribute it and/or modify
- * it under the terms of the GNU General Public License as published by
- * the Free Software Foundation, either version 3 of the License, or
- * (at your option) any later version.
- *
- * Dynare is distributed in the hope that it will be useful,
- * but WITHOUT ANY WARRANTY; without even the implied warranty of
- * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
- * GNU General Public License for more details.
- *
- * You should have received a copy of the GNU General Public License
- * along with Dynare. If not, see <http://www.gnu.org/licenses/>.
- */
-
-#include <cstdlib>
-#include <vector>
-
-#include "Vector.hh"
-#include "Matrix.hh"
-#include "QRDecomposition.hh"
-#include "GeneralizedSchurDecomposition.hh"
-#include "LUSolver.hh"
-
-class DecisionRules
-{
-private:
- const size_t n, p;
- const std::vector<size_t> zeta_fwrd, zeta_back, zeta_mixed, zeta_static;
- const size_t n_fwrd, n_back, n_mixed, n_static, n_back_mixed, n_fwrd_mixed, n_dynamic;
- std::vector<size_t> zeta_fwrd_mixed, zeta_back_mixed, zeta_dynamic,
- beta_back, beta_fwrd, pi_back, pi_fwrd;
- Matrix S, A, D, E, Z_prime;
- QRDecomposition QR;
- GeneralizedSchurDecomposition GSD;
- LUSolver LU1, LU2, LU3;
- Matrix Z21, g_y_back, g_y_back_tmp;
- Matrix g_y_static, A0s, A0d, g_y_dynamic, g_y_static_tmp;
- Matrix g_u_tmp1, g_u_tmp2;
- LUSolver LU4;
-public:
- class BlanchardKahnException
- {
- public:
- //! True if the model fails the order condition. False if it fails the rank condition.
- const bool order;
- const int n_fwrd_vars, n_explosive_eigenvals;
- BlanchardKahnException(bool order_arg, int n_fwrd_vars_arg, int n_explosive_eigenvals_arg) : order(order_arg), n_fwrd_vars(n_fwrd_vars_arg), n_explosive_eigenvals(n_explosive_eigenvals_arg) {};
- };
- /*!
- The zetas are supposed to follow C convention (first vector index is zero).
- */
- DecisionRules(size_t n_arg, size_t p_arg, const std::vector<size_t> &zeta_fwrd_arg,
- const std::vector<size_t> &zeta_back_arg, const std::vector<size_t> &zeta_mixed_arg,
- const std::vector<size_t> &zeta_static_arg, double qz_criterium);
- virtual ~DecisionRules(){};
-
- /*!
- \param jacobian First columns are backetermined vars at t-1 (in the order of zeta_back_mixed), then all vars at t (in the orig order), then forward vars at t+1 (in the order of zeta_fwrd_mixed), then exogenous vars.
- */
- void compute(const Matrix &jacobian, Matrix &g_y, Matrix &g_u) throw (BlanchardKahnException, GeneralizedSchurDecomposition::GSDException);
- template<class Vec1, class Vec2>
- void getGeneralizedEigenvalues(Vec1 &eig_real, Vec2 &eig_cmplx);
-};
-
-std::ostream &operator<<(std::ostream &out, const DecisionRules::BlanchardKahnException &e);
-
-template<class Vec1, class Vec2>
-void
-DecisionRules::getGeneralizedEigenvalues(Vec1 &eig_real, Vec2 &eig_cmplx)
-{
- GSD.getGeneralizedEigenvalues(eig_real, eig_cmplx);
-}
diff --git a/mex/sources/estimation/DetrendData.cc b/mex/sources/estimation/DetrendData.cc
deleted file mode 100644
index 928e789598670326f41c42841e4aee026ecb0744..0000000000000000000000000000000000000000
--- a/mex/sources/estimation/DetrendData.cc
+++ /dev/null
@@ -1,39 +0,0 @@
-/*
- * Copyright (C) 2009-2010 Dynare Team
- *
- * This file is part of Dynare.
- *
- * Dynare is free software: you can redistribute it and/or modify
- * it under the terms of the GNU General Public License as published by
- * the Free Software Foundation, either version 3 of the License, or
- * (at your option) any later version.
- *
- * Dynare is distributed in the hope that it will be useful,
- * but WITHOUT ANY WARRANTY; without even the implied warranty of
- * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
- * GNU General Public License for more details.
- *
- * You should have received a copy of the GNU General Public License
- * along with Dynare. If not, see <http://www.gnu.org/licenses/>.
- */
-
-///////////////////////////////////////////////////////////
-// DetrendData.cpp
-// Implementation of the Class DetrendData
-// Created on: 02-Feb-2010 13:01:15
-///////////////////////////////////////////////////////////
-
-#include "DetrendData.hh"
-
-DetrendData::DetrendData(const bool INlogLinear) //, Vector& INtrendCoeff)
- : logLinear(INlogLinear) //trendCoeff(INtrendCoeff)
-{
-};
-
-void
-DetrendData::detrend(const VectorView &SteadyState, const MatrixConstView &dataView,
- MatrixView &detrendedDataView)
-{
- detrendedDataView = dataView;
-};
-
diff --git a/mex/sources/estimation/DetrendData.hh b/mex/sources/estimation/DetrendData.hh
deleted file mode 100644
index 5f26d9f69d8505fbc6f0185ef0bb84f3bf2d19e0..0000000000000000000000000000000000000000
--- a/mex/sources/estimation/DetrendData.hh
+++ /dev/null
@@ -1,44 +0,0 @@
-/*
- * Copyright (C) 2009-2010 Dynare Team
- *
- * This file is part of Dynare.
- *
- * Dynare is free software: you can redistribute it and/or modify
- * it under the terms of the GNU General Public License as published by
- * the Free Software Foundation, either version 3 of the License, or
- * (at your option) any later version.
- *
- * Dynare is distributed in the hope that it will be useful,
- * but WITHOUT ANY WARRANTY; without even the implied warranty of
- * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
- * GNU General Public License for more details.
- *
- * You should have received a copy of the GNU General Public License
- * along with Dynare. If not, see <http://www.gnu.org/licenses/>.
- */
-///////////////////////////////////////////////////////////
-// DetrendData.h
-// Implementation of the Class DetrendData
-// Created on: 02-Feb-2010 13:01:15
-///////////////////////////////////////////////////////////
-
-#if !defined(DetrendData_312823A1_6248_4af0_B204_DB22F1237E9B__INCLUDED_)
-#define DetrendData_312823A1_6248_4af0_B204_DB22F1237E9B__INCLUDED_
-
-#include "Matrix.hh"
-
-class DetrendData
-{
-
-public:
- virtual ~DetrendData(){};
- DetrendData(const bool logLinear); // add later Vector& trendCoeff);
- void detrend(const VectorView &SteadyState, const MatrixConstView &dataView, MatrixView &detrendedDataView);
-
-private:
- const bool logLinear;
- //Vector trendCoeff;
-
-};
-
-#endif // !defined(312823A1_6248_4af0_B204_DB22F1237E9B__INCLUDED_)
diff --git a/mex/sources/estimation/EstimatedParameter.cc b/mex/sources/estimation/EstimatedParameter.cc
deleted file mode 100644
index bf59ae15601f2612dd21f7844266b3f49a15cdc2..0000000000000000000000000000000000000000
--- a/mex/sources/estimation/EstimatedParameter.cc
+++ /dev/null
@@ -1,40 +0,0 @@
-/*
- * Copyright (C) 2009-2011 Dynare Team
- *
- * This file is part of Dynare.
- *
- * Dynare is free software: you can redistribute it and/or modify
- * it under the terms of the GNU General Public License as published by
- * the Free Software Foundation, either version 3 of the License, or
- * (at your option) any later version.
- *
- * Dynare is distributed in the hope that it will be useful,
- * but WITHOUT ANY WARRANTY; without even the implied warranty of
- * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
- * GNU General Public License for more details.
- *
- * You should have received a copy of the GNU General Public License
- * along with Dynare. If not, see <http://www.gnu.org/licenses/>.
- */
-
-///////////////////////////////////////////////////////////
-// EstimatedParameter.cpp
-// Implementation of the Class EstimatedParameter
-// Created on: 02-Feb-2010 13:06:35
-///////////////////////////////////////////////////////////
-
-#include "EstimatedParameter.hh"
-
-EstimatedParameter::EstimatedParameter(const EstimatedParameter::pType type_arg,
- size_t ID1_arg, size_t ID2_arg, const std::vector<size_t> &subSampleIDs_arg,
- double lower_bound_arg, double upper_bound_arg, Prior *prior_arg) :
- ptype(type_arg), ID1(ID1_arg), ID2(ID2_arg),
- lower_bound(lower_bound_arg), upper_bound(upper_bound_arg), prior(prior_arg),
- subSampleIDs(subSampleIDs_arg)
-{
-}
-
-EstimatedParameter::~EstimatedParameter()
-{
-}
-
diff --git a/mex/sources/estimation/EstimatedParameter.hh b/mex/sources/estimation/EstimatedParameter.hh
deleted file mode 100644
index e323b125bbf5178590f6348da93884709c047f42..0000000000000000000000000000000000000000
--- a/mex/sources/estimation/EstimatedParameter.hh
+++ /dev/null
@@ -1,59 +0,0 @@
-/*
- * Copyright (C) 2009-2011 Dynare Team
- *
- * This file is part of Dynare.
- *
- * Dynare is free software: you can redistribute it and/or modify
- * it under the terms of the GNU General Public License as published by
- * the Free Software Foundation, either version 3 of the License, or
- * (at your option) any later version.
- *
- * Dynare is distributed in the hope that it will be useful,
- * but WITHOUT ANY WARRANTY; without even the implied warranty of
- * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
- * GNU General Public License for more details.
- *
- * You should have received a copy of the GNU General Public License
- * along with Dynare. If not, see <http://www.gnu.org/licenses/>.
- */
-///////////////////////////////////////////////////////////
-// EstimatedParameter.h
-// Implementation of the Class EstimatedParameter
-// Created on: 02-Feb-2010 13:06:35
-///////////////////////////////////////////////////////////
-
-#if !defined(D879C8AE_5B69_4fc3_83BD_FA5A99030ECF__INCLUDED_)
-#define D879C8AE_5B69_4fc3_83BD_FA5A99030ECF__INCLUDED_
-
-#include "Prior.hh"
-#include <cstdlib>
-#include <vector>
-struct EstimatedParameter
-{
-public:
- // parameter types
- enum pType
- {
- shock_SD = 1, // standard deviation of a structural shock
- measureErr_SD = 2, // standard deviation of a measurement error
- shock_Corr = 3, // correlation betwwen two structural shocks
- measureErr_Corr = 4, // correlation between two measurement errors
- deepPar = 5 // deep parameter
- };
-
- EstimatedParameter(const EstimatedParameter::pType type,
- size_t ID1, size_t ID2, const std::vector<size_t> &subSampleIDs,
- double lower_bound, double upper_bound, Prior *prior
- );
- virtual ~EstimatedParameter();
-
- enum pType ptype;
- size_t ID1;
- size_t ID2;
- double lower_bound;
- double upper_bound;
- Prior *prior;
- std::vector<size_t> subSampleIDs;
-};
-
-#endif // !defined(D879C8AE_5B69_4fc3_83BD_FA5A99030ECF__INCLUDED_)
diff --git a/mex/sources/estimation/EstimatedParametersDescription.cc b/mex/sources/estimation/EstimatedParametersDescription.cc
deleted file mode 100644
index ff73894cdc7861f4021392b0346a747267a9311a..0000000000000000000000000000000000000000
--- a/mex/sources/estimation/EstimatedParametersDescription.cc
+++ /dev/null
@@ -1,48 +0,0 @@
-/*
- * Copyright (C) 2010 Dynare Team
- *
- * This file is part of Dynare.
- *
- * Dynare is free software: you can redistribute it and/or modify
- * it under the terms of the GNU General Public License as published by
- * the Free Software Foundation, either version 3 of the License, or
- * (at your option) any later version.
- *
- * Dynare is distributed in the hope that it will be useful,
- * but WITHOUT ANY WARRANTY; without even the implied warranty of
- * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
- * GNU General Public License for more details.
- *
- * You should have received a copy of the GNU General Public License
- * along with Dynare. If not, see <http://www.gnu.org/licenses/>.
- */
-
-///////////////////////////////////////////////////////////
-// EstimatedParametersDescription.cpp
-// Implementation of the Class EstimatedParametersDescription
-// Created on: 02-Feb-2010 13:06:47
-///////////////////////////////////////////////////////////
-
-#include "EstimatedParametersDescription.hh"
-
-EstimatedParametersDescription::~EstimatedParametersDescription()
-{
-}
-
-EstimatedParametersDescription::EstimatedParametersDescription(std::vector<EstimationSubsample> &INestSubsamples, std::vector<EstimatedParameter> &INestParams) :
- estSubsamples(INestSubsamples), estParams(INestParams)
-{
-}
-
-size_t
-EstimatedParametersDescription::getNumberOfPeriods() const
-{
- size_t r = 0;
- for (size_t i = 0; i < estSubsamples.size(); i++)
- {
- size_t r2 = estSubsamples[i].endPeriod + 1;
- if (r2 > r)
- r = r2;
- }
- return r;
-}
diff --git a/mex/sources/estimation/EstimatedParametersDescription.hh b/mex/sources/estimation/EstimatedParametersDescription.hh
deleted file mode 100644
index 0e4a14fac672406ae228f6660ff1d17d23466ad2..0000000000000000000000000000000000000000
--- a/mex/sources/estimation/EstimatedParametersDescription.hh
+++ /dev/null
@@ -1,55 +0,0 @@
-/*
- * Copyright (C) 2009-2010 Dynare Team
- *
- * This file is part of Dynare.
- *
- * Dynare is free software: you can redistribute it and/or modify
- * it under the terms of the GNU General Public License as published by
- * the Free Software Foundation, either version 3 of the License, or
- * (at your option) any later version.
- *
- * Dynare is distributed in the hope that it will be useful,
- * but WITHOUT ANY WARRANTY; without even the implied warranty of
- * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
- * GNU General Public License for more details.
- *
- * You should have received a copy of the GNU General Public License
- * along with Dynare. If not, see <http://www.gnu.org/licenses/>.
- */
-///////////////////////////////////////////////////////////
-// EstimatedParametersDescription.h
-// Implementation of the Class EstimatedParametersDescription
-// Created on: 02-Feb-2010 13:06:46
-///////////////////////////////////////////////////////////
-
-#if !defined(E8F2C096_A301_42e8_80FF_A643291BF995__INCLUDED_)
-#define E8F2C096_A301_42e8_80FF_A643291BF995__INCLUDED_
-
-#include "EstimationSubsample.hh"
-#include "EstimatedParameter.hh"
-#include "Prior.hh"
-
-/**
- * all estimation periods held in the vectors of EstPeriod-s are held in the
- * EstimatedParametersDescription together with the time-invariant attributes (e.g.
- * IDs..) for integration..
- *
- * The EstimatedParametersDescription. structure (or class with protected
- * elements) integrates all parametr and time period information and makes it
- * available to (friend ?) class LogPosteriorDensity on as needed basis and
- * updates all parameters (inc. H and Q) when time slot xparam1 is supplied.
- *
- *
- *
- */
-class EstimatedParametersDescription
-{
-public:
- virtual ~EstimatedParametersDescription();
- EstimatedParametersDescription(std::vector<EstimationSubsample> &estSubsamples, std::vector<EstimatedParameter> &estParams);
- std::vector<EstimationSubsample> estSubsamples;
- std::vector<EstimatedParameter> estParams;
- size_t getNumberOfPeriods() const;
-};
-
-#endif // !defined(E8F2C096_A301_42e8_80FF_A643291BF995__INCLUDED_)
diff --git a/mex/sources/estimation/EstimationSubsample.cc b/mex/sources/estimation/EstimationSubsample.cc
deleted file mode 100644
index f8e937377e84c305c3246a89a88c7981e0767aac..0000000000000000000000000000000000000000
--- a/mex/sources/estimation/EstimationSubsample.cc
+++ /dev/null
@@ -1,36 +0,0 @@
-/*
- * Copyright (C) 2009-2010 Dynare Team
- *
- * This file is part of Dynare.
- *
- * Dynare is free software: you can redistribute it and/or modify
- * it under the terms of the GNU General Public License as published by
- * the Free Software Foundation, either version 3 of the License, or
- * (at your option) any later version.
- *
- * Dynare is distributed in the hope that it will be useful,
- * but WITHOUT ANY WARRANTY; without even the implied warranty of
- * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
- * GNU General Public License for more details.
- *
- * You should have received a copy of the GNU General Public License
- * along with Dynare. If not, see <http://www.gnu.org/licenses/>.
- */
-
-///////////////////////////////////////////////////////////
-// EstimationSubsample.cpp
-// Implementation of the Class EstimationSubsample
-// Created on: 02-Feb-2010 13:06:01
-///////////////////////////////////////////////////////////
-
-#include "EstimationSubsample.hh"
-
-EstimationSubsample::EstimationSubsample(size_t INstartPeriod, size_t INendPeriod) :
- startPeriod(INstartPeriod), endPeriod(INendPeriod)
-{
-}
-
-EstimationSubsample::~EstimationSubsample()
-{
-}
-
diff --git a/mex/sources/estimation/EstimationSubsample.hh b/mex/sources/estimation/EstimationSubsample.hh
deleted file mode 100644
index 5d76e1293e5e3bd896970721106ab1c2c0914ca6..0000000000000000000000000000000000000000
--- a/mex/sources/estimation/EstimationSubsample.hh
+++ /dev/null
@@ -1,73 +0,0 @@
-/*
- * Copyright (C) 2009-2011 Dynare Team
- *
- * This file is part of Dynare.
- *
- * Dynare is free software: you can redistribute it and/or modify
- * it under the terms of the GNU General Public License as published by
- * the Free Software Foundation, either version 3 of the License, or
- * (at your option) any later version.
- *
- * Dynare is distributed in the hope that it will be useful,
- * but WITHOUT ANY WARRANTY; without even the implied warranty of
- * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
- * GNU General Public License for more details.
- *
- * You should have received a copy of the GNU General Public License
- * along with Dynare. If not, see <http://www.gnu.org/licenses/>.
- */
-
-///////////////////////////////////////////////////////////
-// EstimationSubsample.h
-// Implementation of the Class EstimationSubsample
-// Created on: 02-Feb-2010 13:06:01
-///////////////////////////////////////////////////////////
-
-#if !defined(EstSub34FB1351_4066_4993_B384_56AA65BC32C4__INCLUDED_)
-#define EstSub34FB1351_4066_4993_B384_56AA65BC32C4__INCLUDED_
-
-#include <cstdlib>
-#include <vector>
-
-/**
- * Contains longest common periods for different parameters with different start
- * and end periods:
- *
- * It defines start and end of that period.which has start higher/equal than any
- * individual parameter start and its end lower|equal than any individual
- * parameter end in that perod window.) integrated xparam1 and priors for that
- * period
- *
- * All those EstPeriod-s need to be constructed at some point once at a start of
- * estimation by EstPeriod costructor from the information such as invidual
- * parameter start-end periods and the relevant associated priors for those
- * periods. That initial info-set is held in the vector of vectors of
- * EstParamSubSampleDescription
- *
- * it constructs and contains indices of all estimated xparam1 parameters valid
- * for this period in the larger, extended xparam1x vector passed in. from the
- * gradient function.
- *
- * The EstimatedParametersDescription. structure (or class with protected
- * elements) integrates all that information and makes it available to (friend ?)
- * class LogPosteriorDensity on as needed basis and updates all parameters (inc. H
- * and Q) when time slot xparam1 is supplied.
- *
- * Time indices follow C convention: first period has index 0.
- */
-class EstimationSubsample
-{
-public:
- EstimationSubsample(size_t startPeriod, size_t endPeriod);
- virtual ~EstimationSubsample();
-
- size_t startPeriod;
- size_t endPeriod;
- /**
- * indices of all estimated xparam1 parameters valid for this period in the larger,
- * extended xparam1x vector passed in. from the gradient function will be added at a later stage of development
- */
- // const std::vector<size_t> subSampleParamIDs;
-};
-
-#endif // !defined(34FB1351_4066_4993_B384_56AA65BC32C4__INCLUDED_)
diff --git a/mex/sources/estimation/InitializeKalmanFilter.cc b/mex/sources/estimation/InitializeKalmanFilter.cc
deleted file mode 100644
index 57373820a034f351ed2b39f315696bef70213615..0000000000000000000000000000000000000000
--- a/mex/sources/estimation/InitializeKalmanFilter.cc
+++ /dev/null
@@ -1,104 +0,0 @@
-/*
- * Copyright (C) 2010-2012 Dynare Team
- *
- * This file is part of Dynare.
- *
- * Dynare is free software: you can redistribute it and/or modify
- * it under the terms of the GNU General Public License as published by
- * the Free Software Foundation, either version 3 of the License, or
- * (at your option) any later version.
- *
- * Dynare is distributed in the hope that it will be useful,
- * but WITHOUT ANY WARRANTY; without even the implied warranty of
- * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
- * GNU General Public License for more details.
- *
- * You should have received a copy of the GNU General Public License
- * along with Dynare. If not, see <http://www.gnu.org/licenses/>.
- */
-
-///////////////////////////////////////////////////////////
-// InitializeKalmanFilter.cpp
-// Implementation of the Class InitializeKalmanFilter
-// Created on: 02-Feb-2010 12:25:28
-///////////////////////////////////////////////////////////
-
-#include "InitializeKalmanFilter.hh"
-#include "BlasBindings.hh"
-
-InitializeKalmanFilter::~InitializeKalmanFilter()
-{
-}
-
-InitializeKalmanFilter::InitializeKalmanFilter(const std::string &dynamicDllFile, size_t n_endo_arg, size_t n_exo_arg,
- const std::vector<size_t> &zeta_fwrd_arg, const std::vector<size_t> &zeta_back_arg,
- const std::vector<size_t> &zeta_mixed_arg, const std::vector<size_t> &zeta_static_arg,
- const std::vector<size_t> &zeta_varobs_back_mixed_arg,
- double qz_criterium_arg,
- double lyapunov_tol_arg, int &info) :
- lyapunov_tol(lyapunov_tol_arg),
- zeta_varobs_back_mixed(zeta_varobs_back_mixed_arg),
- detrendData(false), modelSolution(dynamicDllFile, n_endo_arg, n_exo_arg, zeta_fwrd_arg, zeta_back_arg,
- zeta_mixed_arg, zeta_static_arg, qz_criterium_arg),
- discLyapFast(zeta_varobs_back_mixed.size()),
- g_x(n_endo_arg, zeta_back_arg.size() + zeta_mixed_arg.size()),
- g_u(n_endo_arg, n_exo_arg),
- Rt(n_exo_arg, zeta_varobs_back_mixed.size()),
- RQ(zeta_varobs_back_mixed.size(), n_exo_arg)
-{
- std::vector<size_t> zeta_back_mixed;
- set_union(zeta_back_arg.begin(), zeta_back_arg.end(),
- zeta_mixed_arg.begin(), zeta_mixed_arg.end(),
- back_inserter(zeta_back_mixed));
- for (size_t i = 0; i < zeta_back_mixed.size(); i++)
- pi_bm_vbm.push_back(find(zeta_varobs_back_mixed.begin(), zeta_varobs_back_mixed.end(),
- zeta_back_mixed[i]) - zeta_varobs_back_mixed.begin());
-
-}
-void
-InitializeKalmanFilter::setT(Matrix &T, int &info)
-{
- // Initialize the empty columns of T to zero
- T.setAll(0.0);
- mat::assignByVectors(T, mat::nullVec, pi_bm_vbm, g_x, zeta_varobs_back_mixed, mat::nullVec);
-}
-
-void
-InitializeKalmanFilter::setRQR(Matrix &R, const MatrixView &Q, Matrix &RQRt, int &info)
-{
- mat::assignByVectors(R, mat::nullVec, mat::nullVec, g_u, zeta_varobs_back_mixed, mat::nullVec);
-
- // Matrix RQRt=R*Q*R'
- blas::gemm("N", "N", 1.0, R, Q, 0.0, RQ); // R*Q
- blas::gemm("N", "T", 1.0, RQ, R, 0.0, RQRt); // R*Q*R'
-}
-
-void
-InitializeKalmanFilter::setPstar(Matrix &Pstar, Matrix &Pinf, const Matrix &T, const Matrix &RQRt, int &info)
-{
-
- try
- {
- // disclyap_fast(T, RQR, Pstar, lyapunov_tol, 0 or 1 to check chol)
- discLyapFast.solve_lyap(T, RQRt, Pstar, lyapunov_tol, 0);
-
- Pinf.setAll(0.0);
- }
- catch (const DiscLyapFast::DLPException &e)
- {
- if (e.info > 0) // The matrix is not positive definite in NormCholesky calculator
- {
- puts(e.message.c_str());
- info = -1; //likelihood = penalty;
- return;
- }
- else if (e.info < 0)
- {
- printf("Caugth unhandled TS exception with Pstar matrix: ");
- puts(e.message.c_str());
- info = -1; //likelihood = penalty;
- throw;
- }
- }
-}
-
diff --git a/mex/sources/estimation/InitializeKalmanFilter.hh b/mex/sources/estimation/InitializeKalmanFilter.hh
deleted file mode 100644
index 25c6f6eb2b7b206d4180a7821aaf74c089a5091f..0000000000000000000000000000000000000000
--- a/mex/sources/estimation/InitializeKalmanFilter.hh
+++ /dev/null
@@ -1,94 +0,0 @@
-/*
- * Copyright (C) 2010-2012 Dynare Team
- *
- * This file is part of Dynare.
- *
- * Dynare is free software: you can redistribute it and/or modify
- * it under the terms of the GNU General Public License as published by
- * the Free Software Foundation, either version 3 of the License, or
- * (at your option) any later version.
- *
- * Dynare is distributed in the hope that it will be useful,
- * but WITHOUT ANY WARRANTY; without even the implied warranty of
- * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
- * GNU General Public License for more details.
- *
- * You should have received a copy of the GNU General Public License
- * along with Dynare. If not, see <http://www.gnu.org/licenses/>.
- */
-
-///////////////////////////////////////////////////////////
-// InitializeKalmanFilter.h
-// Implementation of the Class InitializeKalmanFilter
-// Created on: 02-Feb-2010 12:25:28
-///////////////////////////////////////////////////////////
-
-#if !defined(C3D996B8_22AB_4b77_B693_BA4777AFB091__INCLUDED_)
-#define C3D996B8_22AB_4b77_B693_BA4777AFB091__INCLUDED_
-
-#include "DetrendData.hh"
-#include "ModelSolution.hh"
-#include "DiscLyapFast.hh"
-#include <string>
-
-/**
- * if model is declared stationary ?compute covariance matrix of endogenous
- * variables () by doubling algorithm
- *
- */
-class InitializeKalmanFilter
-{
-
-public:
- /*!
- \param[in] zeta_varobs_back_mixed_arg The union of indices of observed, backward and mixed variables
- */
- InitializeKalmanFilter(const std::string &dynamicDllFile, size_t n_endo, size_t n_exo, const std::vector<size_t> &zeta_fwrd_arg,
- const std::vector<size_t> &zeta_back_arg, const std::vector<size_t> &zeta_mixed_arg, const std::vector<size_t> &zeta_static_arg,
- const std::vector<size_t> &zeta_varobs_back_mixed_arg,
- double qz_criterium_arg, double lyapunov_tol_arg, int &info);
- virtual ~InitializeKalmanFilter();
- // initialise parameter dependent KF matrices only but not Ps
- template <class VEC>
- void initialize(VEC &steadyState, const VectorView &deepParams, Matrix &R,
- const MatrixView &Q, Matrix &RQRt, Matrix &T,
- double &penalty, const MatrixConstView &dataView,
- MatrixView &detrendedDataView, int &info)
- {
- modelSolution.compute(steadyState, deepParams, g_x, g_u);
- detrendData.detrend(steadyState, dataView, detrendedDataView);
-
- setT(T, info);
- setRQR(R, Q, RQRt, info);
- }
-
- // initialise all KF matrices
- template <class VEC>
- void initialize(VEC &steadyState, const VectorView &deepParams, Matrix &R,
- const MatrixView &Q, Matrix &RQRt, Matrix &T, Matrix &Pstar, Matrix &Pinf,
- double &penalty, const MatrixConstView &dataView,
- MatrixView &detrendedDataView, int &info)
- {
- initialize(steadyState, deepParams, R, Q, RQRt, T, penalty, dataView, detrendedDataView, info);
- setPstar(Pstar, Pinf, T, RQRt, info);
- }
-
-private:
- const double lyapunov_tol;
- const std::vector<size_t> zeta_varobs_back_mixed;
- //! Indices of back+mixed zetas inside varobs+back+mixed zetas
- std::vector<size_t> pi_bm_vbm;
-
- DetrendData detrendData;
- ModelSolution modelSolution;
- DiscLyapFast discLyapFast; //Lyapunov solver
- Matrix g_x;
- Matrix g_u;
- Matrix Rt, RQ;
- void setT(Matrix &T, int &info);
- void setRQR(Matrix &R, const MatrixView &Q, Matrix &RQRt, int &info);
- void setPstar(Matrix &Pstar, Matrix &Pinf, const Matrix &T, const Matrix &RQRt, int &info);
-
-};
-
-#endif // !defined(C3D996B8_22AB_4b77_B693_BA4777AFB091__INCLUDED_)
diff --git a/mex/sources/estimation/KalmanFilter.cc b/mex/sources/estimation/KalmanFilter.cc
deleted file mode 100644
index 5b416e1e921273ceb484f581e3da09b79649d815..0000000000000000000000000000000000000000
--- a/mex/sources/estimation/KalmanFilter.cc
+++ /dev/null
@@ -1,197 +0,0 @@
-/*
- * Copyright (C) 2009-2012 Dynare Team
- *
- * This file is part of Dynare.
- *
- * Dynare is free software: you can redistribute it and/or modify
- * it under the terms of the GNU General Public License as published by
- * the Free Software Foundation, either version 3 of the License, or
- * (at your option) any later version.
- *
- * Dynare is distributed in the hope that it will be useful,
- * but WITHOUT ANY WARRANTY; without even the implied warranty of
- * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
- * GNU General Public License for more details.
- *
- * You should have received a copy of the GNU General Public License
- * along with Dynare. If not, see <http://www.gnu.org/licenses/>.
- */
-
-///////////////////////////////////////////////////////////
-// KalmanFilter.cpp
-// Implementation of the Class KalmanFilter
-// Created on: 02-Feb-2010 12:44:41
-///////////////////////////////////////////////////////////
-
-#include "KalmanFilter.hh"
-#include "LapackBindings.hh"
-
-KalmanFilter::~KalmanFilter()
-{
-
-}
-
-KalmanFilter::KalmanFilter(const std::string &dynamicDllFile, size_t n_endo, size_t n_exo,
- const std::vector<size_t> &zeta_fwrd_arg, const std::vector<size_t> &zeta_back_arg,
- const std::vector<size_t> &zeta_mixed_arg, const std::vector<size_t> &zeta_static_arg,
- double qz_criterium_arg, const std::vector<size_t> &varobs_arg,
- double riccati_tol_arg, double lyapunov_tol_arg, int &info) :
- zeta_varobs_back_mixed(compute_zeta_varobs_back_mixed(zeta_back_arg, zeta_mixed_arg, varobs_arg)),
- Z(varobs_arg.size(), zeta_varobs_back_mixed.size()), Zt(Z.getCols(), Z.getRows()), T(zeta_varobs_back_mixed.size()), R(zeta_varobs_back_mixed.size(), n_exo),
- Pstar(zeta_varobs_back_mixed.size(), zeta_varobs_back_mixed.size()), Pinf(zeta_varobs_back_mixed.size(), zeta_varobs_back_mixed.size()),
- RQRt(zeta_varobs_back_mixed.size(), zeta_varobs_back_mixed.size()), Ptmp(zeta_varobs_back_mixed.size(), zeta_varobs_back_mixed.size()), F(varobs_arg.size(), varobs_arg.size()),
- Finv(varobs_arg.size(), varobs_arg.size()), K(zeta_varobs_back_mixed.size(), varobs_arg.size()), KFinv(zeta_varobs_back_mixed.size(), varobs_arg.size()),
- oldKFinv(zeta_varobs_back_mixed.size(), varobs_arg.size()), a_init(zeta_varobs_back_mixed.size()),
- a_new(zeta_varobs_back_mixed.size()), vt(varobs_arg.size()), vtFinv(varobs_arg.size()), riccati_tol(riccati_tol_arg),
- initKalmanFilter(dynamicDllFile, n_endo, n_exo, zeta_fwrd_arg, zeta_back_arg, zeta_mixed_arg,
- zeta_static_arg, zeta_varobs_back_mixed, qz_criterium_arg, lyapunov_tol_arg, info),
- FUTP(varobs_arg.size()*(varobs_arg.size()+1)/2)
-{
- Z.setAll(0.0);
- Zt.setAll(0.0);
- for (size_t i = 0; i < varobs_arg.size(); ++i)
- {
- size_t j = find(zeta_varobs_back_mixed.begin(), zeta_varobs_back_mixed.end(),
- varobs_arg[i]) - zeta_varobs_back_mixed.begin();
- Z(i, j) = 1.0;
- Zt(j, i) = 1.0;
- }
-}
-
-std::vector<size_t>
-KalmanFilter::compute_zeta_varobs_back_mixed(const std::vector<size_t> &zeta_back_arg, const std::vector<size_t> &zeta_mixed_arg, const std::vector<size_t> &varobs_arg)
-{
- std::vector<size_t> varobs_sorted = varobs_arg;
- sort(varobs_sorted.begin(), varobs_sorted.end());
- std::vector<size_t> zeta_back_mixed, zeta_varobs_back_mixed;
- set_union(zeta_back_arg.begin(), zeta_back_arg.end(),
- zeta_mixed_arg.begin(), zeta_mixed_arg.end(),
- back_inserter(zeta_back_mixed));
- set_union(zeta_back_mixed.begin(), zeta_back_mixed.end(),
- varobs_sorted.begin(), varobs_sorted.end(),
- back_inserter(zeta_varobs_back_mixed));
- return zeta_varobs_back_mixed;
-}
-
-
-/**
- * Multi-variate standard Kalman Filter
- */
-double
-KalmanFilter::filter(const MatrixView &detrendedDataView, const Matrix &H, VectorView &vll, size_t start, int &info)
-{
- double loglik = 0.0, ll, logFdet = 0.0, Fdet, dvtFinvVt;
- size_t p = Finv.getRows();
- bool nonstationary = true;
- a_init.setAll(0.0);
- for (size_t t = 0; t < detrendedDataView.getCols(); ++t)
- {
- if (nonstationary)
- {
- // K=PZ'
- //blas::gemm("N", "T", 1.0, Pstar, Z, 0.0, K);
- blas::symm("L", "U", 1.0, Pstar, Zt, 0.0, K);
-
- //F=ZPZ' +H = ZK+H
- F = H;
- blas::gemm("N", "N", 1.0, Z, K, 1.0, F);
- // logFdet=log|F|
-
- // Finv=inv(F)
- mat::set_identity(Finv);
- // Pack F upper trinagle as vector
- for (size_t i = 1; i <= p; ++i)
- for (size_t j = i; j <= p; ++j)
- FUTP(i + (j-1)*j/2 -1) = F(i-1, j-1);
-
- info = lapack::choleskySolver(FUTP, Finv, "U"); // F now contains its Chol decomposition!
- if (info < 0)
- {
- std::cout << "Info:" << info << std::endl;
- std::cout << "t:" << t << std::endl;
- return 0;
- }
- if (info > 0)
- {
- //enforce Pstar symmetry with P=(P+P')/2=0.5P+0.5P'
- mat::transpose(Ptmp, Pstar);
- mat::add(Pstar, Ptmp);
- for (size_t i = 0; i < Pstar.getCols(); ++i)
- for (size_t j = 0; j < Pstar.getCols(); ++j)
- Pstar(i, j) *= 0.5;
-
- // K=PZ'
- //blas::gemm("N", "T", 1.0, Pstar, Z, 0.0, K);
- blas::symm("L", "U", 1.0, Pstar, Zt, 0.0, K);
-
- //F=ZPZ' +H = ZK+H
- F = H;
- blas::gemm("N", "N", 1.0, Z, K, 1.0, F);
-
- // Finv=inv(F)
- mat::set_identity(Finv);
- // Pack F upper trinagle as vector
- for (size_t i = 1; i <= p; ++i)
- for (size_t j = i; j <= p; ++j)
- FUTP(i + (j-1)*j/2 -1) = F(i-1, j-1);
-
- info = lapack::choleskySolver(FUTP, Finv, "U"); // F now contains its Chol decomposition!
- if (info != 0)
- {
- return 0;
- }
- }
- // KFinv gain matrix
- blas::symm("R", "U", 1.0, Finv, K, 0.0, KFinv);
- // deteminant of F:
- Fdet = 1;
- for (size_t d = 1; d <= p; ++d)
- Fdet *= FUTP(d + (d-1)*d/2 -1);
- Fdet *= Fdet;
-
- logFdet = log(fabs(Fdet));
-
- Ptmp = Pstar;
- // Pt+1= T(Pt - KFinvK')T' +RQR'
- // 1) Ptmp= Pt - K*FinvK'
- blas::gemm("N", "T", -1.0, KFinv, K, 1.0, Ptmp);
- // 2) Ptmp= T*Ptmp
- Pstar = Ptmp;
- //blas::gemm("N", "N", 1.0, T, Pstar, 0.0, Ptmp);
- blas::symm("R", "U", 1.0, Pstar, T, 0.0, Ptmp);
- // 3) Pt+1= Ptmp*T' +RQR'
- Pstar = RQRt;
- blas::gemm("N", "T", 1.0, Ptmp, T, 1.0, Pstar);
-
- if (t > 0)
- nonstationary = mat::isDiff(KFinv, oldKFinv, riccati_tol);
- oldKFinv = KFinv;
- }
-
- // err= Yt - Za
- VectorConstView yt = mat::get_col(detrendedDataView, t);
- vt = yt;
- blas::gemv("N", -1.0, Z, a_init, 1.0, vt);
-
- // at+1= T(at+ KFinv *err)
- blas::gemv("N", 1.0, KFinv, vt, 1.0, a_init);
- blas::gemv("N", 1.0, T, a_init, 0.0, a_new);
- a_init = a_new;
-
- /*****************
- Here we calc likelihood and store results.
- *****************/
- blas::symv("U", 1.0, Finv, vt, 0.0, vtFinv);
- dvtFinvVt = blas::dot(vtFinv, vt);
-
- ll = -0.5*(p*log(2*M_PI)+logFdet+dvtFinvVt);
-
- vll(t) = ll;
- if (t >= start)
- loglik += ll;
-
- }
-
- return loglik;
-}
-
diff --git a/mex/sources/estimation/KalmanFilter.hh b/mex/sources/estimation/KalmanFilter.hh
deleted file mode 100644
index 6a688e2f1ff95a198a443832ffce54ef713f3337..0000000000000000000000000000000000000000
--- a/mex/sources/estimation/KalmanFilter.hh
+++ /dev/null
@@ -1,112 +0,0 @@
-/*
- * Copyright (C) 2009-2012 Dynare Team
- *
- * This file is part of Dynare.
- *
- * Dynare is free software: you can redistribute it and/or modify
- * it under the terms of the GNU General Public License as published by
- * the Free Software Foundation, either version 3 of the License, or
- * (at your option) any later version.
- *
- * Dynare is distributed in the hope that it will be useful,
- * but WITHOUT ANY WARRANTY; without even the implied warranty of
- * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
- * GNU General Public License for more details.
- *
- * You should have received a copy of the GNU General Public License
- * along with Dynare. If not, see <http://www.gnu.org/licenses/>.
- */
-
-///////////////////////////////////////////////////////////
-// KalmanFilter.h
-// Implementation of the Class KalmanFilter
-// Created on: 02-Feb-2010 12:44:41
-///////////////////////////////////////////////////////////
-
-#if !defined(KF_213B0417_532B_4027_9EDF_36C004CB4CD1__INCLUDED_)
-#define KF_213B0417_532B_4027_9EDF_36C004CB4CD1__INCLUDED_
-
-#include "InitializeKalmanFilter.hh"
-
-/**
- * Vanilla Kalman filter without constant and with measurement error (use scalar
- * 0 when no measurement error).
- * If multivariate filter is faster, do as in Matlab: start with multivariate
- * filter and switch to univariate filter only in case of singularity
- *
- * mamber functions: compute() and filter()
- * OUTPUT
- * LIK: likelihood
- *
- * REFERENCES
- * See "Filtering and Smoothing of State Vector for Diffuse State Space
- * Models", S.J. Koopman and J. Durbin (2003, in Journal of Time Series
- * Analysis, vol. 24(1), pp. 85-98).
- */
-
-class KalmanFilter
-{
-
-public:
- virtual ~KalmanFilter();
- KalmanFilter(const std::string &dynamicDllFile, size_t n_endo, size_t n_exo, const std::vector<size_t> &zeta_fwrd_arg,
- const std::vector<size_t> &zeta_back_arg, const std::vector<size_t> &zeta_mixed_arg, const std::vector<size_t> &zeta_static_arg,
- double qz_criterium_arg, const std::vector<size_t> &varobs_arg,
- double riccati_tol_arg, double lyapunov_tol_arg, int &info);
-
- template <class VEC>
- double compute(const MatrixConstView &dataView, VEC &steadyState,
- const MatrixView &Q, const Matrix &H, const VectorView &deepParams,
- VectorView &vll, MatrixView &detrendedDataView, size_t start, size_t period,
- double &penalty, int &info)
- {
- double lik = INFINITY;
- try
- {
- if (period == 0) // initialise all KF matrices
- initKalmanFilter.initialize(steadyState, deepParams, R, Q, RQRt, T, Pstar, Pinf,
- penalty, dataView, detrendedDataView, info);
- else // initialise parameter dependent KF matrices only but not Ps
- initKalmanFilter.initialize(steadyState, deepParams, R, Q, RQRt, T,
- penalty, dataView, detrendedDataView, info);
-
- lik = filter(detrendedDataView, H, vll, start, info);
- }
- catch (const DecisionRules::BlanchardKahnException &bke)
- {
- info = 22;
- return penalty;
- }
-
- if (info != 0)
- return penalty;
- else
- return lik;
-
- };
-
-private:
- const std::vector<size_t> zeta_varobs_back_mixed;
- static std::vector<size_t> compute_zeta_varobs_back_mixed(const std::vector<size_t> &zeta_back_arg, const std::vector<size_t> &zeta_mixed_arg, const std::vector<size_t> &varobs_arg);
- Matrix Z, Zt; //nob*mm matrix mapping endogeneous variables and observations and its transpose
- Matrix T; //mm*mm transition matrix of the state equation.
- Matrix R; //mm*rr matrix, mapping structural innovations to state variables.
- Matrix Pstar; //mm*mm variance-covariance matrix of stationary variables
- Matrix Pinf; //mm*mm variance-covariance matrix of diffuse variables
- // allocate space for intermediary matrices
- Matrix RQRt, Ptmp; //mm*mm variance-covariance matrix of variable disturbances
- Matrix F, Finv; // nob*nob F=ZPZt +H an inv(F)
- Matrix K, KFinv, oldKFinv; // mm*nobs K=PZt and K*Finv gain matrices
- Vector a_init, a_new; // state vector
- Vector vt; // current observation error vectors
- Vector vtFinv; // intermediate observation error *Finv vector
- double riccati_tol;
- InitializeKalmanFilter initKalmanFilter; //Initialise KF matrices
- Vector FUTP; // F upper triangle packed as vector FUTP(i + (j-1)*j/2) = F(i,j) for 1<=i<=j;
-
- // Method
- double filter(const MatrixView &detrendedDataView, const Matrix &H, VectorView &vll, size_t start, int &info);
-
-};
-
-#endif // !defined(213B0417_532B_4027_9EDF_36C004CB4CD1__INCLUDED_)
diff --git a/mex/sources/estimation/LogLikelihoodMain.cc b/mex/sources/estimation/LogLikelihoodMain.cc
deleted file mode 100644
index 47318726d961b82b3d5e249269ee22aa3b214ec0..0000000000000000000000000000000000000000
--- a/mex/sources/estimation/LogLikelihoodMain.cc
+++ /dev/null
@@ -1,47 +0,0 @@
-/*
- * Copyright (C) 2009-2012 Dynare Team
- *
- * This file is part of Dynare.
- *
- * Dynare is free software: you can redistribute it and/or modify
- * it under the terms of the GNU General Public License as published by
- * the Free Software Foundation, either version 3 of the License, or
- * (at your option) any later version.
- *
- * Dynare is distributed in the hope that it will be useful,
- * but WITHOUT ANY WARRANTY; without even the implied warranty of
- * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
- * GNU General Public License for more details.
- *
- * You should have received a copy of the GNU General Public License
- * along with Dynare. If not, see <http://www.gnu.org/licenses/>.
- */
-
-///////////////////////////////////////////////////////////
-// LogLikelihoodMain.cpp
-// Implementation of the Class LogLikelihoodMain
-// Created on: 02-Feb-2010 12:57:09
-///////////////////////////////////////////////////////////
-
-#include "LogLikelihoodMain.hh"
-
-LogLikelihoodMain::LogLikelihoodMain(const std::string &dynamicDllFile, EstimatedParametersDescription &estiParDesc, size_t n_endo, size_t n_exo,
- const std::vector<size_t> &zeta_fwrd_arg, const std::vector<size_t> &zeta_back_arg,
- const std::vector<size_t> &zeta_mixed_arg, const std::vector<size_t> &zeta_static_arg, const double qz_criterium,
- const std::vector<size_t> &varobs, double riccati_tol, double lyapunov_tol, int &info_arg)
-
- : estSubsamples(estiParDesc.estSubsamples),
- logLikelihoodSubSample(dynamicDllFile, estiParDesc, n_endo, n_exo, zeta_fwrd_arg, zeta_back_arg, zeta_mixed_arg, zeta_static_arg, qz_criterium,
- varobs, riccati_tol, lyapunov_tol, info_arg),
- vll(estiParDesc.getNumberOfPeriods()), // time dimension size of data
- detrendedData(varobs.size(), estiParDesc.getNumberOfPeriods())
-{
-
-}
-
-LogLikelihoodMain::~LogLikelihoodMain()
-{
-
-}
-
-
diff --git a/mex/sources/estimation/LogLikelihoodMain.hh b/mex/sources/estimation/LogLikelihoodMain.hh
deleted file mode 100644
index 88a2b5bfa3cfa64874008a7b1dcb0beb38ef4cf7..0000000000000000000000000000000000000000
--- a/mex/sources/estimation/LogLikelihoodMain.hh
+++ /dev/null
@@ -1,78 +0,0 @@
-/*
- * Copyright (C) 2009-2012 Dynare Team
- *
- * This file is part of Dynare.
- *
- * Dynare is free software: you can redistribute it and/or modify
- * it under the terms of the GNU General Public License as published by
- * the Free Software Foundation, either version 3 of the License, or
- * (at your option) any later version.
- *
- * Dynare is distributed in the hope that it will be useful,
- * but WITHOUT ANY WARRANTY; without even the implied warranty of
- * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
- * GNU General Public License for more details.
- *
- * You should have received a copy of the GNU General Public License
- * along with Dynare. If not, see <http://www.gnu.org/licenses/>.
- */
-///////////////////////////////////////////////////////////
-// LogLikelihoodMain.h
-// Implementation of the Class LogLikelihoodMain
-// Created on: 02-Feb-2010 12:57:09
-///////////////////////////////////////////////////////////
-
-#if !defined(E126AEF5_AC28_400a_821A_3BCFD1BC4C22__INCLUDED_)
-#define E126AEF5_AC28_400a_821A_3BCFD1BC4C22__INCLUDED_
-
-#include "LogLikelihoodSubSample.hh"
-
-class LogLikelihoodMain
-{
-private:
- std::vector<EstimationSubsample> &estSubsamples; // reference to member of EstimatedParametersDescription
- LogLikelihoodSubSample logLikelihoodSubSample;
- Vector vll; // vector of all KF step likelihoods
- Matrix detrendedData;
-
-public:
- virtual ~LogLikelihoodMain();
- LogLikelihoodMain(const std::string &dynamicDllFile, EstimatedParametersDescription &estiParDesc, size_t n_endo, size_t n_exo,
- const std::vector<size_t> &zeta_fwrd_arg, const std::vector<size_t> &zeta_back_arg, const std::vector<size_t> &zeta_mixed_arg,
- const std::vector<size_t> &zeta_static_arg, const double qz_criterium_arg, const std::vector<size_t> &varobs_arg,
- double riccati_tol_arg, double lyapunov_tol_arg, int &info);
-
- /**
- * Compute method Inputs:
- * Matrix &steadyState; Matrix of sub-sample periods column-vectors of steady states, one column vectro for each sub-sample period
- * vectors of deep deepParams and estimated estParams
- * Matrix &data input data reference
- * Q and H KF matrices of shock and measurement error varinaces and covariances
- * KF logLikelihood calculation start period.
- */
-
- template <class VEC1, class VEC2>
- double compute(VEC1 &steadyState, VEC2 &estParams, VectorView &deepParams, const MatrixConstView &data,
- MatrixView &Q, Matrix &H, size_t start, int &info)
- {
- double logLikelihood = 0;
- for (size_t i = 0; i < estSubsamples.size(); ++i)
- {
- VectorView vSteadyState (steadyState,0,steadyState.getSize());
-
- MatrixConstView dataView(data, 0, estSubsamples[i].startPeriod,
- data.getRows(), estSubsamples[i].endPeriod-estSubsamples[i].startPeriod+1);
- MatrixView detrendedDataView(detrendedData, 0, estSubsamples[i].startPeriod,
- data.getRows(), estSubsamples[i].endPeriod-estSubsamples[i].startPeriod+1);
-
- VectorView vllView(vll, estSubsamples[i].startPeriod, estSubsamples[i].endPeriod-estSubsamples[i].startPeriod+1);
- logLikelihood += logLikelihoodSubSample.compute(vSteadyState, dataView, estParams, deepParams,
- Q, H, vllView, detrendedDataView, info, start, i);
- }
- return logLikelihood;
- };
-
- Vector &getVll() { return vll; };
-};
-
-#endif // !defined(E126AEF5_AC28_400a_821A_3BCFD1BC4C22__INCLUDED_)
diff --git a/mex/sources/estimation/LogLikelihoodSubSample.cc b/mex/sources/estimation/LogLikelihoodSubSample.cc
deleted file mode 100644
index 77ad440a40188058a92828d1cb5bb62257ff9b2a..0000000000000000000000000000000000000000
--- a/mex/sources/estimation/LogLikelihoodSubSample.cc
+++ /dev/null
@@ -1,42 +0,0 @@
-/*
- * Copyright (C) 2009-2012 Dynare Team
- *
- * This file is part of Dynare.
- *
- * Dynare is free software: you can redistribute it and/or modify
- * it under the terms of the GNU General Public License as published by
- * the Free Software Foundation, either version 3 of the License, or
- * (at your option) any later version.
- *
- * Dynare is distributed in the hope that it will be useful,
- * but WITHOUT ANY WARRANTY; without even the implied warranty of
- * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
- * GNU General Public License for more details.
- *
- * You should have received a copy of the GNU General Public License
- * along with Dynare. If not, see <http://www.gnu.org/licenses/>.
- */
-
-///////////////////////////////////////////////////////////
-// LogLikelihoodSubSample.cpp
-// Implementation of the Class LogLikelihoodSubSample
-// Created on: 14-Jan-2010 22:39:14
-///////////////////////////////////////////////////////////
-
-//#include "LogLikelihoodSubSample.hh"
-#include "LogLikelihoodMain.hh" // use ...Main.hh for testing only
-
-LogLikelihoodSubSample::~LogLikelihoodSubSample()
-{
-};
-
-LogLikelihoodSubSample::LogLikelihoodSubSample(const std::string &dynamicDllFile, EstimatedParametersDescription &INestiParDesc, size_t n_endo, size_t n_exo,
- const std::vector<size_t> &zeta_fwrd_arg, const std::vector<size_t> &zeta_back_arg,
- const std::vector<size_t> &zeta_mixed_arg, const std::vector<size_t> &zeta_static_arg, const double qz_criterium,
- const std::vector<size_t> &varobs, double riccati_tol, double lyapunov_tol, int &INinfo) :
- startPenalty(-1e8), estiParDesc(INestiParDesc),
- kalmanFilter(dynamicDllFile, n_endo, n_exo, zeta_fwrd_arg, zeta_back_arg, zeta_mixed_arg, zeta_static_arg, qz_criterium,
- varobs, riccati_tol, lyapunov_tol, INinfo), eigQ(n_exo), eigH(varobs.size()), info(INinfo)
-{
-};
-
diff --git a/mex/sources/estimation/LogLikelihoodSubSample.hh b/mex/sources/estimation/LogLikelihoodSubSample.hh
deleted file mode 100644
index ca388c2748c4a7109381c68c6042c40ddfb89f0b..0000000000000000000000000000000000000000
--- a/mex/sources/estimation/LogLikelihoodSubSample.hh
+++ /dev/null
@@ -1,189 +0,0 @@
-/*
- * Copyright (C) 2009-2012 Dynare Team
- *
- * This file is part of Dynare.
- *
- * Dynare is free software: you can redistribute it and/or modify
- * it under the terms of the GNU General Public License as published by
- * the Free Software Foundation, either version 3 of the License, or
- * (at your option) any later version.
- *
- * Dynare is distributed in the hope that it will be useful,
- * but WITHOUT ANY WARRANTY; without even the implied warranty of
- * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
- * GNU General Public License for more details.
- *
- * You should have received a copy of the GNU General Public License
- * along with Dynare. If not, see <http://www.gnu.org/licenses/>.
- */
-
-///////////////////////////////////////////////////////////
-// LogLikelihoodSubSample.h
-// Implementation of the Class LogLikelihoodSubSample
-// Created on: 14-Jan-2010 22:39:14
-///////////////////////////////////////////////////////////
-
-#if !defined(DF8B7AF5_8169_4587_9037_2CD2C82E2DDF__INCLUDED_)
-#define DF8B7AF5_8169_4587_9037_2CD2C82E2DDF__INCLUDED_
-
-#include <algorithm>
-#include "EstimatedParametersDescription.hh"
-#include "KalmanFilter.hh"
-#include "VDVEigDecomposition.hh"
-#include "LapackBindings.hh"
-
-class LogLikelihoodSubSample
-{
-
-public:
- LogLikelihoodSubSample(const std::string &dynamicDllFile, EstimatedParametersDescription &estiParDesc, size_t n_endo, size_t n_exo,
- const std::vector<size_t> &zeta_fwrd_arg, const std::vector<size_t> &zeta_back_arg,
- const std::vector<size_t> &zeta_mixed_arg, const std::vector<size_t> &zeta_static_arg, const double qz_criterium,
- const std::vector<size_t> &varobs_arg, double riccati_tol_in, double lyapunov_tol, int &info);
-
- template <class VEC1, class VEC2>
- double compute(VEC1 &steadyState, const MatrixConstView &dataView, VEC2 &estParams, VectorView &deepParams,
- MatrixView &Q, Matrix &H, VectorView &vll, MatrixView &detrendedDataView, int &info, size_t start, size_t period)
- {
- penalty = startPenalty;
- logLikelihood = startPenalty;
-
- updateParams(estParams, deepParams, Q, H, period);
- if (info == 0)
- logLikelihood = kalmanFilter.compute(dataView, steadyState, Q, H, deepParams, vll, detrendedDataView, start, period, penalty, info);
- // else
- // logLikelihood+=penalty;
-
- return logLikelihood;
-
- };
-
- virtual ~LogLikelihoodSubSample();
-
-private:
- double startPenalty, penalty;
- double logLikelihood;
- EstimatedParametersDescription &estiParDesc;
- KalmanFilter kalmanFilter;
- VDVEigDecomposition eigQ;
- VDVEigDecomposition eigH;
- int &info;
-
- // methods
- template <class VEC>
- void updateParams(VEC &estParams, VectorView &deepParams,
- MatrixView &Q, Matrix &H, size_t period)
- {
- size_t i, k, k1, k2;
- int test;
- bool found;
- std::vector<size_t>::const_iterator it;
- info = 0;
-
- for (i = 0; i < estParams.getSize(); ++i)
- {
- found = false;
- it = find(estiParDesc.estParams[i].subSampleIDs.begin(),
- estiParDesc.estParams[i].subSampleIDs.end(), period);
- if (it != estiParDesc.estParams[i].subSampleIDs.end())
- found = true;
- if (found)
- {
- switch (estiParDesc.estParams[i].ptype)
- {
- case EstimatedParameter::shock_SD:
- k = estiParDesc.estParams[i].ID1;
- Q(k, k) = estParams(i)*estParams(i);
- break;
-
- case EstimatedParameter::measureErr_SD:
- k = estiParDesc.estParams[i].ID1;
- H(k, k) = estParams(i)*estParams(i);
- break;
-
- case EstimatedParameter::shock_Corr:
- k1 = estiParDesc.estParams[i].ID1;
- k2 = estiParDesc.estParams[i].ID2;
- Q(k1, k2) = estParams(i)*sqrt(Q(k1, k1)*Q(k2, k2));
- Q(k2, k1) = Q(k1, k2);
- // [CholQ,testQ] = chol(Q);
- test = lapack::choleskyDecomp(Q, "L");
- if (test > 0)
- {
- mexPrintf("Caugth unhandled exception with cholesky of Q matrix: ");
- logLikelihood = penalty;
- info = 1;
- }
- else if (test < 0)
- {
- // The variance-covariance matrix of the structural innovations is not definite positive.
- // We have to compute the eigenvalues of this matrix in order to build the penalty.
- double delta = 0;
- eigQ.calculate(Q); // get eigenvalues
- //k = find(a < 0);
- if (eigQ.hasConverged())
- {
- const Vector &evQ = eigQ.getD();
- for (i = 0; i < evQ.getSize(); ++i)
- if (evQ(i) < 0)
- delta -= evQ(i);
- }
-
- logLikelihood = penalty+delta;
- info = 43;
- } // if
- break;
-
- case EstimatedParameter::measureErr_Corr:
- k1 = estiParDesc.estParams[i].ID1;
- k2 = estiParDesc.estParams[i].ID2;
- // H(k1,k2) = xparam1(i)*sqrt(H(k1,k1)*H(k2,k2));
- // H(k2,k1) = H(k1,k2);
- H(k1, k2) = estParams(i)*sqrt(H(k1, k1)*H(k2, k2));
- H(k2, k1) = H(k1, k2);
-
- //[CholH,testH] = chol(H);
- test = lapack::choleskyDecomp(H, "L");
- if (test > 0)
- {
- mexPrintf("Caugth unhandled exception with cholesky of Q matrix: ");
- logLikelihood = penalty;
- info = 1;
- }
- else if (test < 0)
- {
- // The variance-covariance matrix of the measurement errors is not definite positive.
- // We have to compute the eigenvalues of this matrix in order to build the penalty.
- //a = diag(eig(H));
- double delta = 0;
- eigH.calculate(H); // get eigenvalues
- //k = find(a < 0);
- if (eigH.hasConverged())
- {
- const Vector &evH = eigH.getD();
- for (i = 0; i < evH.getSize(); ++i)
- if (evH(i) < 0)
- delta -= evH(i);
- }
- logLikelihood = penalty+delta;
- info = 44;
- } // end if
- break;
-
- //if estim_params_.np > 0 // i.e. num of deep parameters >0
- case EstimatedParameter::deepPar:
- k = estiParDesc.estParams[i].ID1;
- deepParams(k) = estParams(i);
- break;
- default:
- logLikelihood = penalty;
- info = 1;
- } // end switch
- } // end found
- } //end for
- };
-
-
-};
-
-#endif // !defined(DF8B7AF5_8169_4587_9037_2CD2C82E2DDF__INCLUDED_)
diff --git a/mex/sources/estimation/LogPosteriorDensity.cc b/mex/sources/estimation/LogPosteriorDensity.cc
deleted file mode 100644
index d938b956580eea8df000ee7323c2175c12ad1ca9..0000000000000000000000000000000000000000
--- a/mex/sources/estimation/LogPosteriorDensity.cc
+++ /dev/null
@@ -1,52 +0,0 @@
-/*
- * Copyright (C) 2009-2012 Dynare Team
- *
- * This file is part of Dynare.
- *
- * Dynare is free software: you can redistribute it and/or modify
- * it under the terms of the GNU General Public License as published by
- * the Free Software Foundation, either version 3 of the License, or
- * (at your option) any later version.
- *
- * Dynare is distributed in the hope that it will be useful,
- * but WITHOUT ANY WARRANTY; without even the implied warranty of
- * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
- * GNU General Public License for more details.
- *
- * You should have received a copy of the GNU General Public License
- * along with Dynare. If not, see <http://www.gnu.org/licenses/>.
- */
-
-///////////////////////////////////////////////////////////
-// LogPosteriorDensity.cpp
-// Implementation of the Class LogPosteriorDensity
-// Created on: 10-Feb-2010 20:54:18
-///////////////////////////////////////////////////////////
-
-#include "LogPosteriorDensity.hh"
-
-LogPosteriorDensity::~LogPosteriorDensity()
-{
-}
-
-LogPosteriorDensity::LogPosteriorDensity(const std::string &modName, EstimatedParametersDescription &estParamsDesc, size_t n_endo, size_t n_exo,
- const std::vector<size_t> &zeta_fwrd_arg, const std::vector<size_t> &zeta_back_arg, const std::vector<size_t> &zeta_mixed_arg,
- const std::vector<size_t> &zeta_static_arg, const double qz_criterium_arg, const std::vector<size_t> &varobs_arg,
- double riccati_tol_arg, double lyapunov_tol_arg, int &info_arg) :
- logPriorDensity(estParamsDesc),
- logLikelihoodMain(modName, estParamsDesc, n_endo, n_exo, zeta_fwrd_arg, zeta_back_arg, zeta_mixed_arg,
- zeta_static_arg, qz_criterium_arg, varobs_arg, riccati_tol_arg, lyapunov_tol_arg, info_arg)
-{
-
-}
-
-
-/**
- * vector of log likelihoods for each Kalman step
- */
-Vector &
-LogPosteriorDensity::getLikVector()
-{
- return logLikelihoodMain.getVll();
-}
-
diff --git a/mex/sources/estimation/LogPosteriorDensity.hh b/mex/sources/estimation/LogPosteriorDensity.hh
deleted file mode 100644
index 4ff4a0d59e372b30f8576230c882d32dc9eff546..0000000000000000000000000000000000000000
--- a/mex/sources/estimation/LogPosteriorDensity.hh
+++ /dev/null
@@ -1,64 +0,0 @@
-/*
- * Copyright (C) 2009-2012 Dynare Team
- *
- * This file is part of Dynare.
- *
- * Dynare is free software: you can redistribute it and/or modify
- * it under the terms of the GNU General Public License as published by
- * the Free Software Foundation, either version 3 of the License, or
- * (at your option) any later version.
- *
- * Dynare is distributed in the hope that it will be useful,
- * but WITHOUT ANY WARRANTY; without even the implied warranty of
- * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
- * GNU General Public License for more details.
- *
- * You should have received a copy of the GNU General Public License
- * along with Dynare. If not, see <http://www.gnu.org/licenses/>.
- */
-
-///////////////////////////////////////////////////////////
-// LogPosteriorDensity.hh
-// Implementation of the Class LogPosteriorDensity
-// Created on: 10-Feb-2010 20:54:18
-///////////////////////////////////////////////////////////
-
-#if !defined(LPD_052A31B5_53BF_4904_AD80_863B52827973__INCLUDED_)
-#define LPD_052A31B5_53BF_4904_AD80_863B52827973__INCLUDED_
-
-#include "EstimatedParametersDescription.hh"
-#include "LogPriorDensity.hh"
-#include "LogLikelihoodMain.hh"
-
-/**
- * Class that calculates Log Posterior Density using kalman, based on Dynare
- * DsgeLikelihood.m
- */
-class LogPosteriorDensity
-{
-
-private:
- LogPriorDensity logPriorDensity;
- LogLikelihoodMain logLikelihoodMain;
-
-public:
- virtual ~LogPosteriorDensity();
-
- LogPosteriorDensity(const std::string &modName, EstimatedParametersDescription &estParamsDesc, size_t n_endo, size_t n_exo,
- const std::vector<size_t> &zeta_fwrd_arg, const std::vector<size_t> &zeta_back_arg, const std::vector<size_t> &zeta_mixed_arg,
- const std::vector<size_t> &zeta_static_arg, const double qz_criterium_arg, const std::vector<size_t> &varobs_arg,
- double riccati_tol_arg, double lyapunov_tol_arg, int &info_arg);
-
- template <class VEC1, class VEC2>
- double
- compute(VEC1 &steadyState, VEC2 &estParams, VectorView &deepParams, const MatrixConstView &data, MatrixView &Q, Matrix &H, size_t presampleStart, int &info)
- {
- return -logLikelihoodMain.compute(steadyState, estParams, deepParams, data, Q, H, presampleStart, info)
- -logPriorDensity.compute(estParams);
- }
-
- Vector&getLikVector();
-
-};
-
-#endif // !defined(052A31B5_53BF_4904_AD80_863B52827973__INCLUDED_)
diff --git a/mex/sources/estimation/LogPriorDensity.cc b/mex/sources/estimation/LogPriorDensity.cc
deleted file mode 100644
index fbdcdc5ac771231b00084fe17bd3db41c0210a2f..0000000000000000000000000000000000000000
--- a/mex/sources/estimation/LogPriorDensity.cc
+++ /dev/null
@@ -1,43 +0,0 @@
-/*
- * Copyright (C) 2009-2012 Dynare Team
- *
- * This file is part of Dynare.
- *
- * Dynare is free software: you can redistribute it and/or modify
- * it under the terms of the GNU General Public License as published by
- * the Free Software Foundation, either version 3 of the License, or
- * (at your option) any later version.
- *
- * Dynare is distributed in the hope that it will be useful,
- * but WITHOUT ANY WARRANTY; without even the implied warranty of
- * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
- * GNU General Public License for more details.
- *
- * You should have received a copy of the GNU General Public License
- * along with Dynare. If not, see <http://www.gnu.org/licenses/>.
- */
-
-///////////////////////////////////////////////////////////
-// LogPriorDensity.cpp
-// Implementation of the Class LogPriorDensity
-// Created on: 10-Feb-2010 20:56:08
-///////////////////////////////////////////////////////////
-
-#include "LogPriorDensity.hh"
-LogPriorDensity::~LogPriorDensity()
-{
-};
-
-LogPriorDensity::LogPriorDensity(EstimatedParametersDescription &estParsDesc_arg) :
- estParsDesc(estParsDesc_arg)
-{
-};
-
-/**
- * Return random number for prior fromits distribution
- */
-void
-LogPriorDensity::computeNewParams(Vector &ep)
-{
-
-}
diff --git a/mex/sources/estimation/LogPriorDensity.hh b/mex/sources/estimation/LogPriorDensity.hh
deleted file mode 100644
index 5a07402be09a93de0b3cbba76da30ddbde03477f..0000000000000000000000000000000000000000
--- a/mex/sources/estimation/LogPriorDensity.hh
+++ /dev/null
@@ -1,61 +0,0 @@
-/*
- * Copyright (C) 2010-2012 Dynare Team
- *
- * This file is part of Dynare.
- *
- * Dynare is free software: you can redistribute it and/or modify
- * it under the terms of the GNU General Public License as published by
- * the Free Software Foundation, either version 3 of the License, or
- * (at your option) any later version.
- *
- * Dynare is distributed in the hope that it will be useful,
- * but WITHOUT ANY WARRANTY; without even the implied warranty of
- * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
- * GNU General Public License for more details.
- *
- * You should have received a copy of the GNU General Public License
- * along with Dynare. If not, see <http://www.gnu.org/licenses/>.
- */
-
-///////////////////////////////////////////////////////////
-// LogPriorDensity.hh
-// Implementation of the Class LogPriorDensity
-// Created on: 10-Feb-2010 20:56:08
-///////////////////////////////////////////////////////////
-
-#if !defined(LPD_011FD4CF_17CE_4805_882B_046AA07CF443__INCLUDED_)
-#define LPD_011FD4CF_17CE_4805_882B_046AA07CF443__INCLUDED_
-
-//#include <boost/random/variate_generator.hpp>
-#include "Vector.hh"
-#include "EstimatedParametersDescription.hh"
-
-class LogPriorDensity
-{
-
-public:
- LogPriorDensity(EstimatedParametersDescription &estParsDesc);
- virtual ~LogPriorDensity();
-
- template<class VEC>
- double compute(VEC &ep)
- {
- assert(estParsDesc.estParams.size() == ep.getSize());
- double logPriorDensity = 0;
- for (size_t i = 0; i < ep.getSize(); ++i)
- {
- logPriorDensity += log(((*(estParsDesc.estParams[i]).prior)).pdf(ep(i)));
- if (std::isinf(fabs(logPriorDensity)))
- return logPriorDensity;
- }
- return logPriorDensity;
- };
-
- void computeNewParams(Vector &newParams);
-
-private:
- const EstimatedParametersDescription &estParsDesc;
-
-};
-
-#endif // !defined(011FD4CF_17CE_4805_882B_046AA07CF443__INCLUDED_)
diff --git a/mex/sources/estimation/Makefile.am b/mex/sources/estimation/Makefile.am
deleted file mode 100644
index f1b7ece1d6f788bcbc033cb7df79b1d3dc878830..0000000000000000000000000000000000000000
--- a/mex/sources/estimation/Makefile.am
+++ /dev/null
@@ -1,43 +0,0 @@
-SUBDIRS = libmat
-
-if HAVE_BLAS
-if HAVE_LAPACK
-SUBDIRS += tests
-endif
-endif
-
-EXTRA_DIST = \
- DecisionRules.cc \
- DecisionRules.hh \
- DetrendData.cc \
- DetrendData.hh \
- EstimatedParameter.cc \
- EstimatedParameter.hh \
- EstimatedParametersDescription.cc \
- EstimatedParametersDescription.hh \
- EstimationSubsample.cc \
- EstimationSubsample.hh \
- InitializeKalmanFilter.cc \
- InitializeKalmanFilter.hh \
- KalmanFilter.cc \
- KalmanFilter.hh \
- LogLikelihoodMain.hh \
- LogLikelihoodMain.cc \
- LogLikelihoodSubSample.cc \
- LogLikelihoodSubSample.hh \
- logMHMCMCposterior.cc \
- logposterior.cc \
- LogPosteriorDensity.cc \
- LogPosteriorDensity.hh \
- LogPriorDensity.cc \
- LogPriorDensity.hh \
- ModelSolution.cc \
- ModelSolution.hh \
- Prior.cc \
- Prior.hh \
- Proposal.cc \
- Proposal.hh \
- RandomWalkMetropolisHastings.hh \
- utils/dynamic_dll.cc \
- utils/dynamic_dll.hh \
- utils/ts_exception.h
diff --git a/mex/sources/estimation/ModelSolution.cc b/mex/sources/estimation/ModelSolution.cc
deleted file mode 100644
index 73066a795d04588ab026f99e6a750822830af43a..0000000000000000000000000000000000000000
--- a/mex/sources/estimation/ModelSolution.cc
+++ /dev/null
@@ -1,54 +0,0 @@
-/*
- * Copyright (C) 2010-2012 Dynare Team
- *
- * This file is part of Dynare.
- *
- * Dynare is free software: you can redistribute it and/or modify
- * it under the terms of the GNU General Public License as published by
- * the Free Software Foundation, either version 3 of the License, or
- * (at your option) any later version.
- *
- * Dynare is distributed in the hope that it will be useful,
- * but WITHOUT ANY WARRANTY; without even the implied warranty of
- * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
- * GNU General Public License for more details.
- *
- * You should have received a copy of the GNU General Public License
- * along with Dynare. If not, see <http://www.gnu.org/licenses/>.
- */
-
-///////////////////////////////////////////////////////////
-// ModelSolution.cpp
-// Implementation of the Class ModelSolution
-// Created on: 02-Feb-2010 13:06:35
-///////////////////////////////////////////////////////////
-
-#include <string>
-
-#include "ModelSolution.hh"
-
-/**
- * compute the steady state (2nd stage), and computes first order approximation
- */
-ModelSolution::ModelSolution(const std::string &dynamicDllFile, size_t n_endo_arg, size_t n_exo_arg, const std::vector<size_t> &zeta_fwrd_arg,
- const std::vector<size_t> &zeta_back_arg, const std::vector<size_t> &zeta_mixed_arg,
- const std::vector<size_t> &zeta_static_arg, double INqz_criterium) :
- n_endo(n_endo_arg), n_exo(n_exo_arg), // n_jcols = Num of Jacobian columns = nStat+2*nPred+3*nBoth+2*nForw+nExog
- n_jcols(n_exo+n_endo+ zeta_back_arg.size() /*nsPred*/ + zeta_fwrd_arg.size() /*nsForw*/ +2*zeta_mixed_arg.size()),
- jacobian(n_endo, n_jcols), residual(n_endo), Mx(1, n_exo),
- decisionRules(n_endo_arg, n_exo_arg, zeta_fwrd_arg, zeta_back_arg, zeta_mixed_arg, zeta_static_arg, INqz_criterium),
- dynamicDLLp(dynamicDllFile, n_exo),
- llXsteadyState(n_jcols-n_exo)
-{
- Mx.setAll(0.0);
- jacobian.setAll(0.0);
-
- set_union(zeta_fwrd_arg.begin(), zeta_fwrd_arg.end(),
- zeta_mixed_arg.begin(), zeta_mixed_arg.end(),
- back_inserter(zeta_fwrd_mixed));
- set_union(zeta_back_arg.begin(), zeta_back_arg.end(),
- zeta_mixed_arg.begin(), zeta_mixed_arg.end(),
- back_inserter(zeta_back_mixed));
-}
-
-
diff --git a/mex/sources/estimation/ModelSolution.hh b/mex/sources/estimation/ModelSolution.hh
deleted file mode 100644
index 3e690ffa66450a7ca24f8011c7e37f8bd34ab408..0000000000000000000000000000000000000000
--- a/mex/sources/estimation/ModelSolution.hh
+++ /dev/null
@@ -1,100 +0,0 @@
-/*
- * Copyright (C) 2010-2012 Dynare Team
- *
- * This file is part of Dynare.
- *
- * Dynare is free software: you can redistribute it and/or modify
- * it under the terms of the GNU General Public License as published by
- * the Free Software Foundation, either version 3 of the License, or
- * (at your option) any later version.
- *
- * Dynare is distributed in the hope that it will be useful,
- * but WITHOUT ANY WARRANTY; without even the implied warranty of
- * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
- * GNU General Public License for more details.
- *
- * You should have received a copy of the GNU General Public License
- * along with Dynare. If not, see <http://www.gnu.org/licenses/>.
- */
-
-///////////////////////////////////////////////////////////
-// ComputeModelSolution.h
-// Implementation of the Class ModelSolution
-// Created on: 15-Jan-2010 07:37:47
-///////////////////////////////////////////////////////////
-
-#if !defined(ModelSolution_5ADFF920_9C74_46f5_9FE9_88AD4D4BBF19__INCLUDED_)
-#define ModelSolution_5ADFF920_9C74_46f5_9FE9_88AD4D4BBF19__INCLUDED_
-
-#include "DecisionRules.hh"
-#include "dynamic_dll.hh"
-
-/**
- * compute the steady state (2nd stage), and
- * computes first order approximation
- *
- */
-class ModelSolution
-{
-
-public:
- ModelSolution(const std::string &dynamicDllFile, size_t n_endo, size_t n_exo, const std::vector<size_t> &zeta_fwrd_arg,
- const std::vector<size_t> &zeta_back_arg, const std::vector<size_t> &zeta_mixed_arg,
- const std::vector<size_t> &zeta_static_arg, double qz_criterium);
- virtual ~ModelSolution() {};
- template <class VEC>
- void compute(VEC &steadyState, const VectorView &deepParams, Matrix &ghx, Matrix &ghu) throw (DecisionRules::BlanchardKahnException, GeneralizedSchurDecomposition::GSDException)
- {
- // compute Steady State
- ComputeSteadyState(steadyState, deepParams);
-
- // then get jacobian and
-
- ComputeModelSolution(steadyState, deepParams, ghx, ghu);
-
- }
-
-private:
- const size_t n_endo;
- const size_t n_exo;
- const size_t n_jcols; // Num of Jacobian columns
- std::vector<size_t> zeta_fwrd_mixed, zeta_back_mixed;
- Matrix jacobian;
- Vector residual;
- Matrix Mx;
- DecisionRules decisionRules;
- DynamicModelDLL dynamicDLLp;
- Vector llXsteadyState;
- //Matrix jacobian;
- template <class VEC>
- void ComputeModelSolution(VEC &steadyState, const VectorView &deepParams,
- Matrix &ghx, Matrix &ghu)
- throw (DecisionRules::BlanchardKahnException, GeneralizedSchurDecomposition::GSDException)
- {
- // set extended Steady State
-
- for (size_t i = 0; i < zeta_back_mixed.size(); i++)
- llXsteadyState(i) = steadyState(zeta_back_mixed[i]);
-
- for (size_t i = 0; i < n_endo; i++)
- llXsteadyState(zeta_back_mixed.size() + i) = steadyState(i);
-
- for (size_t i = 0; i < zeta_fwrd_mixed.size(); i++)
- llXsteadyState(zeta_back_mixed.size() + n_endo + i) = steadyState(zeta_fwrd_mixed[i]);
-
- //get jacobian
- dynamicDLLp.eval(llXsteadyState, Mx, deepParams, steadyState, residual, &jacobian, NULL, NULL);
-
- //compute rules
- decisionRules.compute(jacobian, ghx, ghu);
- }
- template <class VEC>
- void ComputeSteadyState(VEC &steadyState, const VectorView &deepParams)
- {
- // does nothig for time being.
- }
-
-
-};
-
-#endif // !defined(5ADFF920_9C74_46f5_9FE9_88AD4D4BBF19__INCLUDED_)
diff --git a/mex/sources/estimation/Prior.cc b/mex/sources/estimation/Prior.cc
deleted file mode 100644
index 1272a39c033774835b49f9ef57b6f65d9e29b8ee..0000000000000000000000000000000000000000
--- a/mex/sources/estimation/Prior.cc
+++ /dev/null
@@ -1,57 +0,0 @@
-/*
- * Copyright (C) 2009-2010 Dynare Team
- *
- * This file is part of Dynare.
- *
- * Dynare is free software: you can redistribute it and/or modify
- * it under the terms of the GNU General Public License as published by
- * the Free Software Foundation, either version 3 of the License, or
- * (at your option) any later version.
- *
- * Dynare is distributed in the hope that it will be useful,
- * but WITHOUT ANY WARRANTY; without even the implied warranty of
- * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
- * GNU General Public License for more details.
- *
- * You should have received a copy of the GNU General Public License
- * along with Dynare. If not, see <http://www.gnu.org/licenses/>.
- */
-
-///////////////////////////////////////////////////////////
-// Prior.cpp
-// Implementation of the Class Prior
-// Created on: 02-Feb-2010 13:06:20
-///////////////////////////////////////////////////////////
-
-#include "Prior.hh"
-
-Prior::Prior(double mean_arg, double standard_arg, double lower_bound_arg, double upper_bound_arg, double fhp_arg, double shp_arg) :
- mean(mean_arg), standard(standard_arg), lower_bound(lower_bound_arg), upper_bound(upper_bound_arg), fhp(fhp_arg), shp(shp_arg)
-{
-
-}
-
-Prior::~Prior()
-{
-
-}
-
-Prior *
-Prior::constructPrior(pShape shape, double mean, double standard, double lower_bound, double upper_bound, double fhp, double shp)
-{
- switch (shape)
- {
- case Beta:
- return new BetaPrior(mean, standard, lower_bound, upper_bound, fhp, shp);
- case Gamma:
- return new GammaPrior(mean, standard, lower_bound, upper_bound, fhp, shp);
- case Gaussian:
- return new GaussianPrior(mean, standard, lower_bound, upper_bound, fhp, shp);
- case Inv_gamma_1:
- return new InvGamma1_Prior(mean, standard, lower_bound, upper_bound, fhp, shp);
- case Uniform:
- return new UniformPrior(mean, standard, lower_bound, upper_bound, fhp, shp);
- case Inv_gamma_2:
- return new InvGamma2_Prior(mean, standard, lower_bound, upper_bound, fhp, shp);
- }
-}
diff --git a/mex/sources/estimation/Prior.hh b/mex/sources/estimation/Prior.hh
deleted file mode 100644
index de29bf7898716075fb0b4b3d2593e74a9ea57c62..0000000000000000000000000000000000000000
--- a/mex/sources/estimation/Prior.hh
+++ /dev/null
@@ -1,302 +0,0 @@
-/*
- * Copyright (C) 2009-2011 Dynare Team
- *
- * This file is part of Dynare.
- *
- * Dynare is free software: you can redistribute it and/or modify
- * it under the terms of the GNU General Public License as published by
- * the Free Software Foundation, either version 3 of the License, or
- * (at your option) any later version.
- *
- * Dynare is distributed in the hope that it will be useful,
- * but WITHOUT ANY WARRANTY; without even the implied warranty of
- * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
- * GNU General Public License for more details.
- *
- * You should have received a copy of the GNU General Public License
- * along with Dynare. If not, see <http://www.gnu.org/licenses/>.
- */
-
-///////////////////////////////////////////////////////////
-// Prior.h
-// Implementation of the Class Prior
-// Created on: 02-Feb-2010 13:06:20
-///////////////////////////////////////////////////////////
-
-#if !defined(Prior_8D5F562F_C831_43f3_B390_5C4EF4433756__INCLUDED_)
-#define Prior_8D5F562F_C831_43f3_B390_5C4EF4433756__INCLUDED_
-
-#include <boost/random/linear_congruential.hpp>
-#include <boost/random/normal_distribution.hpp>
-#include <boost/random/uniform_real.hpp>
-#include <boost/random/variate_generator.hpp>
-
-#include <boost/math/distributions/beta.hpp> // for beta_distribution.
-#include <boost/math/distributions/gamma.hpp> // for gamma_distribution.
-#include <boost/math/distributions/normal.hpp> // for normal_distribution.
-#include <boost/math/distributions/uniform.hpp> // for uniform_distribution.
-
-// typedef for base_uniform_generator_type
-// rend48 seems better than the basic minstd_rand but
-// one my later try ecuyer1988 or taus88 which are better but not yet supported in the Boost versionwe use
-typedef boost::rand48 base_uniform_generator_type;
-
-struct Prior
-{
-
-public:
- //! probablity density functions
- enum pShape
- {
- Beta = 1,
- Gamma = 2,
- Gaussian = 3, // i.e. Normal density
- Inv_gamma_1 = 4, // Inverse gamma (type 1) density
- Uniform = 5,
- Inv_gamma_2 = 6 //Inverse gamma (type 2) density
- };
-
- Prior(double mean, double standard, double lower_bound, double upper_bound, double fhp, double shp);
- virtual ~Prior();
-
- const double mean;
- const double standard;
- const double lower_bound;
- const double upper_bound;
- /**
- * first shape parameter
- */
- const double fhp;
- /**
- * second shape parameter
- */
- const double shp;
- virtual pShape getShape() = 0; // e.g. = Beta for beta shape?
-
- virtual double
- pdf(double x) // probability density function value for x
- {
- std::cout << "Parent pdf undefined at parent level" << std::endl;
- return 0.0;
- };
-
- virtual double
- drand() // rand for density
- {
- std::cout << "Parent rand undefined at parent level" << std::endl;
- return 0.0;
- };
-
- static Prior *constructPrior(pShape shape, double mean, double standard, double lower_bound, double upper_bound, double fhp, double shp);
-};
-
-struct BetaPrior : public Prior
-{
-public:
- boost::math::beta_distribution<double> distribution;
-
- BetaPrior(double mean, double standard, double lower_bound, double upper_bound, double fhp, double shp) :
- Prior(mean, standard, lower_bound, upper_bound, fhp, shp),
- distribution(fhp, shp)
- {
- };
- virtual ~BetaPrior(){};
- virtual pShape
- getShape()
- {
- return Prior::Beta;
- }; // e.g. = Beta for beta shape?
-
- virtual double
- pdf(double x)
- {
- double scalled = x;
- if (lower_bound || 1.0-upper_bound)
- scalled = (x- lower_bound)/(upper_bound- lower_bound);
- return boost::math::pdf(distribution, scalled);
- };
-
- virtual double
- drand() // rand for density
- {
- return 0.0;
- };
-};
-
-struct GammaPrior : public Prior
-{
-public:
- boost::math::gamma_distribution<double> distribution;
-
- GammaPrior(double mean, double standard,
- double lower_bound, double upper_bound, double fhp, double shp) :
- Prior(mean, standard, lower_bound, upper_bound, fhp, shp),
- distribution(fhp, shp)
- {
- };
- virtual ~GammaPrior(){};
- virtual pShape
- getShape()
- {
- return Prior::Gamma;
- }; // e.g. = Beta for beta shape?
- virtual double
- pdf(double x)
- {
- return boost::math::pdf(distribution, x- lower_bound);
- };
- virtual double
- drand() // rand for density
- {
- return 0.0;
- };
-};
-
-// X ~ IG1(s,nu) if X = sqrt(Y) where Y ~ IG2(s,nu) and Y = inv(Z) with Z ~ G(nu/2,2/s) (Gamma distribution)
-// i.e. Dynare lpdfig1(x,s,n)= lpdfgam(1/(x*x),n/2,2/s)-2*log(x*x)+log(2*x)
-struct InvGamma1_Prior : public Prior
-{
-public:
- boost::math::gamma_distribution<double> distribution;
- InvGamma1_Prior(double mean, double standard,
- double lower_bound, double upper_bound, double fhp, double shp) :
- Prior(mean, standard, lower_bound, upper_bound, fhp, shp),
- distribution(shp/2, 2/fhp)
- {
- };
- virtual ~InvGamma1_Prior(){};
- virtual pShape
- getShape()
- {
- return Prior::Inv_gamma_1;
- }; // e.g. = Beta for beta shape?
- virtual double
- pdf(double x)
- {
- double scalled = ((x- lower_bound)*(x-lower_bound));
- if (x > lower_bound)
- return (boost::math::pdf(distribution, 1/scalled) / (scalled*scalled))*2*(x-lower_bound);
- else
- return 0;
- };
- virtual double
- drand() // rand for density
- {
- return 0.0;
- };
-};
-
-// If x~InvGamma(a,b) , then 1/x ~Gamma(a,1/b) distribution
-// i.e. Dynare lpdfig2(x*x,n,s) = lpdfgam(1/(x*x),s/2,2/n) - 2*log(x*x)
-struct InvGamma2_Prior : public Prior
-{
-public:
- boost::math::gamma_distribution<double> distribution;
-
- InvGamma2_Prior(double mean, double standard,
- double lower_bound, double upper_bound, double fhp, double shp) :
- Prior(mean, standard, lower_bound, upper_bound, fhp, shp),
- distribution(shp/2, 2/fhp)
- {
- };
- virtual ~InvGamma2_Prior(){};
- virtual pShape
- getShape()
- {
- return Prior::Inv_gamma_2;
- }; // e.g. = Beta for beta shape?
-
- virtual double
- pdf(double x)
- {
- double scalled = x - lower_bound;
- if (scalled > 0)
- return boost::math::pdf(distribution, 1/scalled) / (scalled*scalled);
- else
- return 0;
- };
- virtual double
- drand() // rand for density
- {
- return 0.0;
- };
-};
-
-struct GaussianPrior : public Prior
-{
-private:
- base_uniform_generator_type base_rng_type;
- boost::normal_distribution<double> rng_type;
- boost::variate_generator<base_uniform_generator_type &, boost::normal_distribution<double> > vrng;
-
-public:
- boost::math::normal_distribution<double> distribution;
-
- GaussianPrior(double mean, double standard, double lower_bound, double upper_bound, double fhp, double shp) :
- Prior(mean, standard, lower_bound, upper_bound, fhp, shp),
- rng_type(fhp, shp), // random number generator distribution type (mean, standard)
- vrng(base_rng_type, rng_type), // random variate_generator
- distribution(fhp, shp) //pdf distribution(mean, standard)
- {
- };
- virtual ~GaussianPrior(){};
- virtual pShape
- getShape()
- {
- return Prior::Gaussian;
- }; // e.g. = Beta for beta shape?
- virtual double
- pdf(double x)
- {
- if (x > lower_bound && x < upper_bound)
- return boost::math::pdf(distribution, x);
- else
- return 0;
- };
- virtual double
- drand() // rand for density
- {
- return vrng();
- };
-};
-
-struct UniformPrior : public Prior
-{
-private:
- base_uniform_generator_type base_rng_type;
- boost::uniform_real<> rng_type;
- boost::variate_generator<base_uniform_generator_type &, boost::uniform_real<> > vrng;
-
-public:
- boost::math::uniform_distribution<double> distribution;
-
- UniformPrior(double mean, double standard, double lower_bound, double upper_bound, double fhp, double shp) :
- Prior(mean, standard, lower_bound, upper_bound, fhp, shp),
- rng_type(fhp, shp), // random number generator distribution type
- vrng(base_rng_type, rng_type), // random variate_generator
- distribution(fhp, shp) //pdf distribution(lower_bound, upper_bound)
- {
- };
- virtual ~UniformPrior(){};
- virtual pShape
- getShape()
- {
- return Prior::Uniform;
- }; // e.g. = Beta for beta shape?
- virtual double
- pdf(double x)
- {
- if (x > lower_bound && x < upper_bound)
- return boost::math::pdf(distribution, x);
- else
- return 0;
- };
- virtual double
- drand() // rand for density
- {
- return vrng();
- };
-
-};
-
-#endif // !defined(8D5F562F_C831_43f3_B390_5C4EF4433756__INCLUDED_)
diff --git a/mex/sources/estimation/Proposal.cc b/mex/sources/estimation/Proposal.cc
deleted file mode 100644
index 7e7b633d85d38d923ef4eb7bc27072df7aeb2fab..0000000000000000000000000000000000000000
--- a/mex/sources/estimation/Proposal.cc
+++ /dev/null
@@ -1,91 +0,0 @@
-/*
- * Copyright (C) 2009-2010 Dynare Team
- *
- * This file is part of Dynare.
- *
- * Dynare is free software: you can redistribute it and/or modify
- * it under the terms of the GNU General Public License as published by
- * the Free Software Foundation, either version 3 of the License, or
- * (at your option) any later version.
- *
- * Dynare is distributed in the hope that it will be useful,
- * but WITHOUT ANY WARRANTY; without even the implied warranty of
- * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
- * GNU General Public License for more details.
- *
- * You should have received a copy of the GNU General Public License
- * along with Dynare. If not, see <http://www.gnu.org/licenses/>.
- */
-
-///////////////////////////////////////////////////////////
-// Proposal.cpp
-// Implementation of the Class Proposal
-// Created on: 15-Dec-2010 12:43:49
-///////////////////////////////////////////////////////////
-
-#include "Proposal.hh"
-
-Proposal::Proposal(const VectorConstView &vJscale, const MatrixConstView &covariance) :
- len(covariance.getCols()),
- covarianceCholeskyDecomposition(len),
- newDraw(len),
- uniform_rng_type(0, 1), // uniform random number generator distribution type
- uniformVrng(base_rng, uniform_rng_type), // uniform random variate_generator
- normal_rng_type(0, 1), // normal random number generator distribution type (mean, standard)
- normalVrng(base_rng, normal_rng_type) // normal random variate_generator
-{
- Matrix Jscale(len);
- Matrix DD(len);
- DD = covariance;
-
- lapack::choleskyDecomp(DD, "U");
- Jscale.setAll(0.0);
- for (size_t i = 0; i < len; i++)
- Jscale(i, i) = vJscale(i);
- blas::gemm("N", "N", 1.0, DD, Jscale, 0.0, covarianceCholeskyDecomposition);
-}
-
-void
-Proposal::draw(Vector &mean, Vector &draw)
-{
- assert(len == draw.getSize());
- assert(len == mean.getSize());
-
- draw = mean;
- for (size_t i = 0; i < len; ++i)
- newDraw(i) = normalVrng();
- blas::gemv("T", 1.0, covarianceCholeskyDecomposition, newDraw, 1.0, draw);
-
-}
-
-Matrix &
-Proposal::getVar()
-{
- return covarianceCholeskyDecomposition;
-}
-
-/**
- * set or get if null arguments
- */
-int
-Proposal::seed()
-{
- return curSeed;
-}
-
-void
-Proposal::seed(int newSeed)
-{
- curSeed = newSeed;
- base_rng.seed(curSeed);
-}
-
-/**
- * currently returns uniform for MH sampler,
- */
-double
-Proposal::selectionTestDraw()
-{
- return uniformVrng();
-}
-
diff --git a/mex/sources/estimation/Proposal.hh b/mex/sources/estimation/Proposal.hh
deleted file mode 100644
index 13be358fb11703860839072d7bbf85b40a8f6b3b..0000000000000000000000000000000000000000
--- a/mex/sources/estimation/Proposal.hh
+++ /dev/null
@@ -1,92 +0,0 @@
-/*
- * Copyright (C) 2009-2011 Dynare Team
- *
- * This file is part of Dynare.
- *
- * Dynare is free software: you can redistribute it and/or modify
- * it under the terms of the GNU General Public License as published by
- * the Free Software Foundation, either version 3 of the License, or
- * (at your option) any later version.
- *
- * Dynare is distributed in the hope that it will be useful,
- * but WITHOUT ANY WARRANTY; without even the implied warranty of
- * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
- * GNU General Public License for more details.
- *
- * You should have received a copy of the GNU General Public License
- * along with Dynare. If not, see <http://www.gnu.org/licenses/>.
- */
-
-///////////////////////////////////////////////////////////
-// Proposal.hh
-// Implementation of the Class Proposal
-// Created on: 15-Dec-2010 12:43:49
-///////////////////////////////////////////////////////////
-
-#if !defined(CABFAB46_2FA5_4178_8D1C_05DFEAFB4570__INCLUDED_)
-#define CABFAB46_2FA5_4178_8D1C_05DFEAFB4570__INCLUDED_
-
-/**
- * Proposal class will then have the common, seed initialised base generator
- * (currently congruental rand48) and member functions such as seed, reset (to
- * initial,default value) and have all rand generators we need that generate from
- * that common base: single uniform and normal (either single or multivariate
- * determined by the size of the variance matrix) for now.
- *
- * The rng interfaces will be - a single, selectionTest() currently uniform for MH
- * sampler, draw(mean, newDraw) - single or multivariate parameters (currently
- * from Normal(mean,Sigma)) and poss. also the seed state (set and get), the
- * normal Chol_variance_decomp (constructed using Chol Decomp of init Variance
- * matrix) , as core members .This class will handle the main boost random rng
- * intricacies. See enclosed updated diagram (if ok I will upload it)
- *
- */
-
-#include "Matrix.hh"
-#include "BlasBindings.hh"
-#include "LapackBindings.hh"
-#include <boost/random/linear_congruential.hpp>
-#include <boost/random/normal_distribution.hpp>
-#include <boost/random/uniform_real.hpp>
-#include <boost/random/variate_generator.hpp>
-
-// typedef for base_uniform_generator_type
-// rend48 seems better than the basic minstd_rand but
-// one my later try ecuyer1988 or taus88 which are better but not yet supported in the Boost versionwe use
-typedef boost::rand48 base_uniform_generator_type;
-
-class Proposal
-{
-
-public:
- Proposal();
-
-public:
- Proposal(const VectorConstView &vJscale, const MatrixConstView &covariance);
- virtual ~Proposal() {};
- virtual void draw(Vector &mean, Vector &draw);
- virtual Matrix&getVar();
- virtual int seed();
- virtual void seed(int seedInit);
- virtual double selectionTestDraw();
-
-private:
- size_t len;
- Matrix covarianceCholeskyDecomposition;
- /**
- * Vector of new draws
- *
- */
- Vector newDraw;
-
- base_uniform_generator_type base_rng;
- boost::uniform_real<> uniform_rng_type;
- boost::variate_generator<base_uniform_generator_type &, boost::uniform_real<> > uniformVrng;
- boost::normal_distribution<double> normal_rng_type;
- boost::variate_generator<base_uniform_generator_type &, boost::normal_distribution<double> > normalVrng;
-
- int curSeed;
-
-};
-
-#endif // !defined(CABFAB46_2FA5_4178_8D1C_05DFEAFB4570__INCLUDED_)
diff --git a/mex/sources/estimation/RandomWalkMetropolisHastings.hh b/mex/sources/estimation/RandomWalkMetropolisHastings.hh
deleted file mode 100644
index 5b5c02e9b4a5afe9b72b63903ca254ae7b9a713b..0000000000000000000000000000000000000000
--- a/mex/sources/estimation/RandomWalkMetropolisHastings.hh
+++ /dev/null
@@ -1,117 +0,0 @@
-/*
- * Copyright (C) 2010-2012 Dynare Team
- *
- * This file is part of Dynare.
- *
- * Dynare is free software: you can redistribute it and/or modify
- * it under the terms of the GNU General Public License as published by
- * the Free Software Foundation, either version 3 of the License, or
- * (at your option) any later version.
- *
- * Dynare is distributed in the hope that it will be useful,
- * but WITHOUT ANY WARRANTY; without even the implied warranty of
- * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
- * GNU General Public License for more details.
- *
- * You should have received a copy of the GNU General Public License
- * along with Dynare. If not, see <http://www.gnu.org/licenses/>.
- */
-
-///////////////////////////////////////////////////////////
-// RandomWalkMetropolisHastings.hh
-// Implementation of the Class RandomWalkMetropolisHastings
-// Created on: 07-Sep-2010 15:21:40
-///////////////////////////////////////////////////////////
-
-#if !defined(A6BBC5E0_598E_4863_B7FF_E87320056B80__INCLUDED_)
-#define A6BBC5E0_598E_4863_B7FF_E87320056B80__INCLUDED_
-
-#include <iostream>
-#include <fstream>
-#include "LogPosteriorDensity.hh"
-#include "Proposal.hh"
-
-class RandomWalkMetropolisHastings
-{
-
-private:
- Vector parDraw, newParDraw;
-
-public:
- RandomWalkMetropolisHastings(size_t size) :
- parDraw(size), newParDraw(size)
- {
- };
- virtual ~RandomWalkMetropolisHastings() {};
-
- template<class VEC1>
- double compute(VectorView &mhLogPostDens, MatrixView &mhParams, VEC1 &steadyState,
- Vector &estParams, VectorView &deepParams, const MatrixConstView &data, MatrixView &Q, Matrix &H,
- const size_t presampleStart, int &info, const size_t startDraw, size_t nMHruns,
- LogPosteriorDensity &lpd, Proposal &pDD, EstimatedParametersDescription &epd)
- {
- //streambuf *likbuf, *drawbuf *backup;
- std::ofstream urandfilestr, drawfilestr;
- urandfilestr.open("urand.csv");
- drawfilestr.open("paramdraws.csv");
-
- bool overbound;
- double newLogpost, logpost, urand;
- size_t count, accepted = 0;
- parDraw = estParams;
-
- logpost = -lpd.compute(steadyState, estParams, deepParams, data, Q, H, presampleStart, info);
-
- for (size_t run = startDraw - 1; run < nMHruns; ++run)
- {
- overbound = false;
- pDD.draw(parDraw, newParDraw);
- for (count = 0; count < parDraw.getSize(); ++count)
- {
- overbound = (newParDraw(count) < epd.estParams[count].lower_bound || newParDraw(count) > epd.estParams[count].upper_bound);
- if (overbound)
- {
- newLogpost = -INFINITY;
- break;
- }
- }
- if (!overbound)
- {
- try
- {
- newLogpost = -lpd.compute(steadyState, newParDraw, deepParams, data, Q, H, presampleStart, info);
- }
- catch (const std::exception &e)
- {
- throw; // for now handle the system and other errors higher-up
- }
- catch (...)
- {
- newLogpost = -INFINITY;
- }
- }
- urand = pDD.selectionTestDraw();
- if ((newLogpost > -INFINITY) && log(urand) < newLogpost-logpost)
- {
- parDraw = newParDraw;
- logpost = newLogpost;
- accepted++;
- }
- mat::get_row(mhParams, run) = parDraw;
- mhLogPostDens(run) = logpost;
-
- urandfilestr << urand << "\n"; //","
- for (size_t c = 0; c < newParDraw.getSize()-1; ++c)
- drawfilestr << newParDraw(c) << ",";
- drawfilestr << newParDraw(newParDraw.getSize()-1) << "\n";
- }
-
- urandfilestr.close();
- drawfilestr.close();
-
- return (double) accepted/(nMHruns-startDraw+1);
- };
-
-};
-
-#endif // !defined(A6BBC5E0_598E_4863_B7FF_E87320056B80__INCLUDED_)
diff --git a/mex/sources/estimation/libmat/BlasBindings.hh b/mex/sources/estimation/libmat/BlasBindings.hh
deleted file mode 100644
index 50b246021f6bf6c4d77616314d13a26d029e6d04..0000000000000000000000000000000000000000
--- a/mex/sources/estimation/libmat/BlasBindings.hh
+++ /dev/null
@@ -1,169 +0,0 @@
-/*
- * Copyright (C) 2010-2011 Dynare Team
- *
- * This file is part of Dynare.
- *
- * Dynare is free software: you can redistribute it and/or modify
- * it under the terms of the GNU General Public License as published by
- * the Free Software Foundation, either version 3 of the License, or
- * (at your option) any later version.
- *
- * Dynare is distributed in the hope that it will be useful,
- * but WITHOUT ANY WARRANTY; without even the implied warranty of
- * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
- * GNU General Public License for more details.
- *
- * You should have received a copy of the GNU General Public License
- * along with Dynare. If not, see <http://www.gnu.org/licenses/>.
- */
-
-#ifndef _BLAS_BINDINGS_HH
-#define _BLAS_BINDINGS_HH
-
-#include <dynblas.h>
-
-#include "Vector.hh"
-#include "Matrix.hh"
-
-namespace blas
-{
- /* Level 1 */
-
- //! dot product of two vectors
- template<class Vec1, class Vec2>
- inline double
- dot(const Vec1 &A, Vec2 &B)
- {
- assert(A.getSize() == B.getSize());
- blas_int n = A.getSize();
- blas_int lda = A.getStride(), ldb = B.getStride();
- return ddot(&n, A.getData(), &lda, B.getData(), &ldb);
- }
-
- /* Level 2 */
-
- //! Symmetric rank 1 operation: A = alpha*X*X' + A
- template<class Mat, class Vec>
- inline void
- syr(const char *uplo, double alpha, Vec X, Mat A)
- {
- assert(X.getSize() == A.getCols() && A.getCols() == A.getRows());
- blas_int n = X.getSize();
- blas_int incx = X.getStride();
- blas_int lda = A.getLd();
- dsyr(uplo, &n, &alpha, X.getData(), &incx, A.getData(), &lda);
- }
-
- //! General matrix * vector multiplication
- // c = alpha*A*b + beta*c, or c := alpha*A'*b + beta*c,
- // where alpha and beta are scalars, b and c are vectors and A is an
- // m by n matrix.
- template<class Mat1, class Vec2, class Vec3>
- inline void
- gemv(const char *transa, double alpha, const Mat1 &A,
- const Vec2 &B, double beta, Vec3 &C)
- {
- blas_int m = A.getRows(), n = B.getSize(), k = A.getCols(), l = C.getSize();
- if (*transa == 'T')
- {
- m = A.getCols();
- k = A.getRows();
- }
- assert(m == l);
- assert(k == n);
- blas_int lda = A.getLd(), ldb = B.getStride(), ldc = C.getStride();
- dgemv(transa, &m, &n, &alpha, A.getData(), &lda,
- B.getData(), &ldb, &beta, C.getData(), &ldc);
- }
-
- //! Symmetric matrix * vector multiplication
- // c = alpha*A*b + beta*c,
- // where alpha and beta are scalars, b and c are vectors and A is a
- // m by m symmetric matrix.
- template<class Mat1, class Vec2, class Vec3>
- inline void
- symv(const char *uplo, double alpha, const Mat1 &A,
- const Vec2 &B, double beta, Vec3 &C)
- {
- assert(A.getRows() == A.getCols());
- blas_int n = A.getRows();
- assert(A.getRows() == B.getSize());
- assert(A.getRows() == C.getSize());
- blas_int lda = A.getLd(), ldb = B.getStride(), ldc = C.getStride();
- dsymv(uplo, &n, &alpha, A.getData(), &lda,
- B.getData(), &ldb, &beta, C.getData(), &ldc);
- }
-
- /* Level 3 */
-
- //! General matrix multiplication
- template<class Mat1, class Mat2, class Mat3>
- inline void
- gemm(const char *transa, const char *transb,
- double alpha, const Mat1 &A, const Mat2 &B,
- double beta, Mat3 &C)
- {
- blas_int m = A.getRows(), n = B.getCols(), k = A.getCols();
- if (*transa == 'N')
- {
- if (*transb == 'N')
- {
- assert(A.getRows() == C.getRows());
- assert(A.getCols() == B.getRows());
- assert(B.getCols() == C.getCols());
- }
- else if (*transb == 'T')
- {
- assert(A.getRows() == C.getRows());
- assert(A.getCols() == B.getCols());
- assert(B.getRows() == C.getCols());
- n = B.getRows();
- }
- }
- else if (*transa == 'T')
- {
- m = A.getCols();
- k = A.getRows();
- if (*transb == 'N')
- {
- assert(A.getCols() == C.getRows());
- assert(A.getRows() == B.getRows());
- assert(B.getCols() == C.getCols());
- }
- else if (*transb == 'T')
- {
- assert(A.getCols() == C.getRows());
- assert(A.getRows() == B.getCols());
- assert(B.getRows() == C.getCols());
- n = B.getRows();
- }
- }
- blas_int lda = A.getLd(), ldb = B.getLd(), ldc = C.getLd();
- dgemm(transa, transb, &m, &n, &k, &alpha, A.getData(), &lda,
- B.getData(), &ldb, &beta, C.getData(), &ldc);
- }
-
- //! Symmetric matrix A * (poss. rectangular) matrix B multiplication
- template<class Mat1, class Mat2, class Mat3>
- inline void
- symm(const char *side, const char *uplo,
- double alpha, const Mat1 &A, const Mat2 &B,
- double beta, Mat3 &C)
- {
- assert(A.getRows() == A.getCols());
- assert(B.getRows() == C.getRows());
- assert(B.getCols() == C.getCols());
- if (*side == 'L' || *side == 'l')
- assert(A.getCols() == B.getRows());
- else if (*side == 'R' || *side == 'r')
- assert(A.getRows() == B.getCols());
-
- blas_int m = B.getRows(), n = B.getCols();
- blas_int lda = A.getLd(), ldb = B.getLd(), ldc = C.getLd();
- dsymm(side, uplo, &m, &n, &alpha, A.getData(), &lda,
- B.getData(), &ldb, &beta, C.getData(), &ldc);
- }
-
-} // End of namespace
-
-#endif
diff --git a/mex/sources/estimation/libmat/DiscLyapFast.hh b/mex/sources/estimation/libmat/DiscLyapFast.hh
deleted file mode 100644
index dc08bb8e99eca4a8f6f81e01f58b60f9829f3304..0000000000000000000000000000000000000000
--- a/mex/sources/estimation/libmat/DiscLyapFast.hh
+++ /dev/null
@@ -1,122 +0,0 @@
-/*
- * Copyright (C) 2010-2011 Dynare Team
- *
- * This file is part of Dynare.
- *
- * Dynare is free software: you can redistribute it and/or modify
- * it under the terms of the GNU General Public License as published by
- * the Free Software Foundation, either version 3 of the License, or
- * (at your option) any later version.
- *
- * Dynare is distributed in the hope that it will be useful,
- * but WITHOUT ANY WARRANTY; without even the implied warranty of
- * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
- * GNU General Public License for more details.
- *
- * You should have received a copy of the GNU General Public License
- * along with Dynare. If not, see <http://www.gnu.org/licenses/>.
- */
-
-/****************************************************************
- % a wrapper class for function X=disclyap_fast(G,V,ch)
- %
- % Solve the discrete Lyapunov Equation
- % X=G*X*G'+V
- % Using the Doubling Algorithm
- %
- % If ch is defined then the code will check if the resulting X
- % is positive definite and generate an error message if it is not
- %
- % based on work of Joe Pearlman and Alejandro Justiniano
- % 3/5/2005
- % C++ version 28/07/09 by Dynare team
-****************************************************************/
-
-#if !defined(DiscLyapFast_INCLUDE)
-#define DiscLyapFast_INCLUDE
-
-#include "dynlapack.h"
-#include "Matrix.hh"
-#include "BlasBindings.hh"
-
-class DiscLyapFast
-{
- Matrix A0, A1, Ptmp, P0, P1, I;
-
-public:
- class DLPException
- {
- public:
- const int info;
- std::string message;
- DLPException(int info_arg, std::string message_arg) :
- info(info_arg), message(message_arg)
- {
- };
- };
-
- DiscLyapFast(size_t n) :
- A0(n), A1(n), Ptmp(n), P0(n), P1(n), I(n)
- {
- mat::set_identity(I);
- };
- virtual ~DiscLyapFast() {};
- template <class MatG, class MatV, class MatX >
- void solve_lyap(const MatG &G, const MatV &V, MatX &X, double tol, size_t flag_ch) throw (DLPException);
-
-};
-
-template <class MatG, class MatV, class MatX >
-void
-DiscLyapFast::solve_lyap(const MatG &G, const MatV &V, MatX &X, double tol = 1e-16, size_t flag_ch = 0) throw (DLPException)
-{
- P0 = V;
- P1 = V;
- A0 = G;
-
- const double alpha = 1.0;
- const double half = 0.5;
- const double omega = 0.0;
-
- bool matd = true;
- while (matd) // matrix diff > tol
- {
- //P1=P0+A0*P0*A0';
- // first step Ptmp=P0*A0';
- // DGEMM: C := alpha*op( A )*op( B ) + beta*C,
- blas::gemm("N", "T", alpha, P0, A0, omega, Ptmp);
- // P1=P0+A0*Ptmp;
- blas::gemm("N", "N", alpha, A0, Ptmp, alpha, P1);
- // A1=A0*A0;
- blas::gemm("N", "N", alpha, A0, A0, omega, A1);
-
- // ensure symmetry of P1=(P1+P1')/2;
- Ptmp = P1;
- blas::gemm("T", "N", half, Ptmp, I, half, P1);
-
- // check if max( max( abs( P1 - P0 ) ) )>tol
- matd = mat::isDiffSym(P1, P0, tol);
- P0 = P1;
- A0 = A1;
- } //end while
-
- // ensure symmetry of X=P0=(P0+P0')/2;
- blas::gemm("T", "N", half, P1, I, half, P0);
- X = P0;
-
- // Check that X is positive definite
- if (flag_ch == 1) // calc NormCholesky (P0)
- {
- lapack_int lpinfo = 0;
- lapack_int lrows = P0.getRows();
- lapack_int ldl = P0.getLd();
- dpotrf("L", &lrows, P0.getData(), &ldl, &lpinfo);
- if (lpinfo < 0)
- throw DLPException((int) lpinfo, std::string("DiscLyapFast:Internal error in NormCholesky calculator"));
- else if (lpinfo > 0)
- throw DLPException((int) lpinfo, std::string("DiscLyapFast:The matrix is not positive definite in NormCholesky calculator"));
-
- }
-}
-
-#endif //if !defined(DiscLyapFast_INCLUDE)
diff --git a/mex/sources/estimation/libmat/GeneralizedSchurDecomposition.cc b/mex/sources/estimation/libmat/GeneralizedSchurDecomposition.cc
deleted file mode 100644
index 0b9e5d01b1cbd83f59cf08f453139aacddef6d6e..0000000000000000000000000000000000000000
--- a/mex/sources/estimation/libmat/GeneralizedSchurDecomposition.cc
+++ /dev/null
@@ -1,72 +0,0 @@
-/*
- * Copyright (C) 2010-2011 Dynare Team
- *
- * This file is part of Dynare.
- *
- * Dynare is free software: you can redistribute it and/or modify
- * it under the terms of the GNU General Public License as published by
- * the Free Software Foundation, either version 3 of the License, or
- * (at your option) any later version.
- *
- * Dynare is distributed in the hope that it will be useful,
- * but WITHOUT ANY WARRANTY; without even the implied warranty of
- * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
- * GNU General Public License for more details.
- *
- * You should have received a copy of the GNU General Public License
- * along with Dynare. If not, see <http://www.gnu.org/licenses/>.
- */
-
-#include "GeneralizedSchurDecomposition.hh"
-
-#include <cassert>
-#include <cstdlib>
-
-double GeneralizedSchurDecomposition::criterium_static;
-
-GeneralizedSchurDecomposition::GeneralizedSchurDecomposition(size_t n_arg, double criterium_arg) :
- n(n_arg), criterium(criterium_arg)
-{
- alphar = new double[n];
- alphai = new double[n];
- beta = new double[n];
-
- lwork = 16*n+16; // Same heuristic choice than mjdgges
- work = new double[(int) lwork];
- vsl = new double[n*n];
-
- bwork = new lapack_int[n];
-}
-
-GeneralizedSchurDecomposition::~GeneralizedSchurDecomposition()
-{
- delete[] alphar;
- delete[] alphai;
- delete[] beta;
- delete[] work;
- delete[] vsl;
- delete[] bwork;
-}
-
-lapack_int
-GeneralizedSchurDecomposition::selctg(const double *alphar, const double *alphai, const double *beta)
-{
- return ((*alphar * *alphar + *alphai * *alphai) < criterium_static * *beta * *beta);
-}
-
-std::ostream &
-operator<<(std::ostream &out, const GeneralizedSchurDecomposition::GSDException &e)
-{
- out << "DGGES return code " << e.info << ": ";
- if (e.info < 0)
- out << "argument " << -e.info << " has an illegal value";
- else if (e.info <= e.n)
- out << "the QZ iteration failed";
- else if (e.info == e.n + 1)
- out << "other than QZ iteration failed in DHGEQZ";
- else if (e.info == e.n + 2)
- out << "after reordering, roundoff changed values of some complex eigenvalues so that leading eigenvalues in the Generalized Schur form no longer satisfy SELCTG=TRUE. This could also be caused due to scaling";
- else if (e.info == e.n + 3)
- out << "reordering failed in DTGSEN";
- return out;
-}
diff --git a/mex/sources/estimation/libmat/GeneralizedSchurDecomposition.hh b/mex/sources/estimation/libmat/GeneralizedSchurDecomposition.hh
deleted file mode 100644
index f776ba3330a7f86d4eda22326c23cde261412515..0000000000000000000000000000000000000000
--- a/mex/sources/estimation/libmat/GeneralizedSchurDecomposition.hh
+++ /dev/null
@@ -1,116 +0,0 @@
-/*
- * Copyright (C) 2010 Dynare Team
- *
- * This file is part of Dynare.
- *
- * Dynare is free software: you can redistribute it and/or modify
- * it under the terms of the GNU General Public License as published by
- * the Free Software Foundation, either version 3 of the License, or
- * (at your option) any later version.
- *
- * Dynare is distributed in the hope that it will be useful,
- * but WITHOUT ANY WARRANTY; without even the implied warranty of
- * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
- * GNU General Public License for more details.
- *
- * You should have received a copy of the GNU General Public License
- * along with Dynare. If not, see <http://www.gnu.org/licenses/>.
- */
-
-#include <dynlapack.h>
-
-#include "Vector.hh"
-#include "Matrix.hh"
-
-class GeneralizedSchurDecomposition
-{
-private:
- const size_t n;
- const double criterium;
- lapack_int lwork;
- double *alphar, *alphai, *beta, *vsl, *work;
- lapack_int *bwork;
- static double criterium_static;
- static lapack_int selctg(const double *alphar, const double *alphai, const double *beta);
-public:
- class GSDException
- {
- public:
- const lapack_int info, n;
- GSDException(lapack_int info_arg, lapack_int n_arg) : info(info_arg), n(n_arg) {};
- };
- //! \todo Replace heuristic choice for workspace size by a query to determine the optimal size
- GeneralizedSchurDecomposition(size_t n_arg, double criterium_arg);
- virtual ~GeneralizedSchurDecomposition();
- //! \todo Add a lock around the modification of criterium_static for making it thread-safe
- template<class Mat1, class Mat2, class Mat3>
- void compute(Mat1 &S, Mat2 &T, Mat3 &Z, size_t &sdim) throw (GSDException);
- template<class Mat1, class Mat2, class Mat3, class Mat4, class Mat5>
- /*!
- \param[out] sdim Number of non-explosive generalized eigenvalues
- */
- void compute(const Mat1 &D, const Mat2 &E, Mat3 &S, Mat4 &T, Mat5 &Z, size_t &sdim) throw (GSDException);
- template<class Vec1, class Vec2>
- void getGeneralizedEigenvalues(Vec1 &eig_real, Vec2 &eig_cmplx);
-};
-
-std::ostream &operator<<(std::ostream &out, const GeneralizedSchurDecomposition::GSDException &e);
-
-template<class Mat1, class Mat2, class Mat3>
-void
-GeneralizedSchurDecomposition::compute(Mat1 &S, Mat2 &T, Mat3 &Z, size_t &sdim) throw (GSDException)
-{
- assert(S.getRows() == n && S.getCols() == n
- && T.getRows() == n && T.getCols() == n
- && Z.getRows() == n && Z.getCols() == n);
-
- lapack_int n2 = n;
- lapack_int info, sdim2;
- lapack_int lds = S.getLd(), ldt = T.getLd(), ldz = Z.getLd();
-
- criterium_static = criterium;
- // Here we are forced to give space for left Schur vectors, even if we don't use them, because of a bug in dgges()
- dgges("N", "V", "S", &selctg, &n2, S.getData(), &lds, T.getData(), &ldt,
- &sdim2, alphar, alphai, beta, vsl, &n2, Z.getData(), &ldz,
- work, &lwork, bwork, &info);
-
- if (info != 0)
- throw GSDException(info, n2);
-
- sdim = sdim2;
-}
-
-template<class Mat1, class Mat2, class Mat3, class Mat4, class Mat5>
-void
-GeneralizedSchurDecomposition::compute(const Mat1 &D, const Mat2 &E,
- Mat3 &S, Mat4 &T, Mat5 &Z, size_t &sdim) throw (GSDException)
-{
- assert(D.getRows() == n && D.getCols() == n
- && E.getRows() == n && E.getCols() == n);
- S = D;
- T = E;
- compute(S, T, Z, sdim);
-}
-
-template<class Vec1, class Vec2>
-void
-GeneralizedSchurDecomposition::getGeneralizedEigenvalues(Vec1 &eig_real, Vec2 &eig_cmplx)
-{
- assert(eig_real.getSize() == n && eig_cmplx.getSize() == n);
-
- double *par = alphar, *pai = alphai, *pb = beta,
- *per = eig_real.getData(), *pei = eig_cmplx.getData();
- while (par < alphar + n)
- {
- *per = *par / *pb;
- if (*pai == 0.0 && *pb == 0.0)
- *pei = 0.0;
- else
- *pei = *pai / *pb;
- par++;
- pai++;
- pb++;
- per += eig_real.getStride();
- pei += eig_cmplx.getStride();
- }
-}
diff --git a/mex/sources/estimation/libmat/LUSolver.cc b/mex/sources/estimation/libmat/LUSolver.cc
deleted file mode 100644
index 30033f1ebf9bd74dd005d7dd2356b678e9b04a1e..0000000000000000000000000000000000000000
--- a/mex/sources/estimation/libmat/LUSolver.cc
+++ /dev/null
@@ -1,30 +0,0 @@
-/*
- * Copyright (C) 2010 Dynare Team
- *
- * This file is part of Dynare.
- *
- * Dynare is free software: you can redistribute it and/or modify
- * it under the terms of the GNU General Public License as published by
- * the Free Software Foundation, either version 3 of the License, or
- * (at your option) any later version.
- *
- * Dynare is distributed in the hope that it will be useful,
- * but WITHOUT ANY WARRANTY; without even the implied warranty of
- * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
- * GNU General Public License for more details.
- *
- * You should have received a copy of the GNU General Public License
- * along with Dynare. If not, see <http://www.gnu.org/licenses/>.
- */
-
-#include "LUSolver.hh"
-
-LUSolver::LUSolver(size_t dim_arg) : dim(dim_arg)
-{
- ipiv = new lapack_int[dim];
-}
-
-LUSolver::~LUSolver()
-{
- delete[] ipiv;
-}
diff --git a/mex/sources/estimation/libmat/LUSolver.hh b/mex/sources/estimation/libmat/LUSolver.hh
deleted file mode 100644
index e78c18c74327799b5a370a34e36a062e06824198..0000000000000000000000000000000000000000
--- a/mex/sources/estimation/libmat/LUSolver.hh
+++ /dev/null
@@ -1,63 +0,0 @@
-/*
- * Copyright (C) 2010 Dynare Team
- *
- * This file is part of Dynare.
- *
- * Dynare is free software: you can redistribute it and/or modify
- * it under the terms of the GNU General Public License as published by
- * the Free Software Foundation, either version 3 of the License, or
- * (at your option) any later version.
- *
- * Dynare is distributed in the hope that it will be useful,
- * but WITHOUT ANY WARRANTY; without even the implied warranty of
- * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
- * GNU General Public License for more details.
- *
- * You should have received a copy of the GNU General Public License
- * along with Dynare. If not, see <http://www.gnu.org/licenses/>.
- */
-
-#include <cstdlib>
-#include <cassert>
-
-#include <dynlapack.h>
-
-class LUSolver
-{
-private:
- const size_t dim;
- lapack_int *ipiv;
-public:
- class LUException
- {
- public:
- const lapack_int info;
- LUException(lapack_int info_arg) : info(info_arg) {};
- };
- LUSolver(size_t dim_arg);
- virtual ~LUSolver();
- /*!
- Computes A^(-1)*B (possibly transposing A).
- The output is stored in B.
- The input matrix A is modified.
- */
- template<class Mat1, class Mat2>
- void invMult(const char *trans, Mat1 &A, Mat2 &B) throw (LUException);
-};
-
-template<class Mat1, class Mat2>
-void
-LUSolver::invMult(const char *trans, Mat1 &A, Mat2 &B) throw (LUException)
-{
- assert(A.getRows() == dim && A.getCols() == dim);
- assert(B.getRows() == dim);
- lapack_int n = dim, lda = A.getLd(), info;
- dgetrf(&n, &n, A.getData(), &lda, ipiv, &info);
-
- if (info != 0)
- throw LUException(info);
-
- lapack_int nrhs = B.getCols(), ldb = B.getLd();
- dgetrs(trans, &n, &nrhs, A.getData(), &lda, ipiv, B.getData(), &ldb, &info);
- assert(info == 0);
-}
diff --git a/mex/sources/estimation/libmat/LapackBindings.hh b/mex/sources/estimation/libmat/LapackBindings.hh
deleted file mode 100644
index 2755cf0a1bdda13c2806b32d74431ee058c9fb60..0000000000000000000000000000000000000000
--- a/mex/sources/estimation/libmat/LapackBindings.hh
+++ /dev/null
@@ -1,65 +0,0 @@
-/*
- * Copyright (C) 2010-2011 Dynare Team
- *
- * This file is part of Dynare.
- *
- * Dynare is free software: you can redistribute it and/or modify
- * it under the terms of the GNU General Public License as published by
- * the Free Software Foundation, either version 3 of the License, or
- * (at your option) any later version.
- *
- * Dynare is distributed in the hope that it will be useful,
- * but WITHOUT ANY WARRANTY; without even the implied warranty of
- * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
- * GNU General Public License for more details.
- *
- * You should have received a copy of the GNU General Public License
- * along with Dynare. If not, see <http://www.gnu.org/licenses/>.
- */
-
-#ifndef _LAPACK_BINDINGS_HH
-#define _LAPACK_BINDINGS_HH
-
-#include <dynlapack.h>
-
-#include "Vector.hh"
-#include "Matrix.hh"
-
-namespace lapack
-{
- // calc Cholesky Decomposition (Mat A, char "U"pper/"L"ower)
- template<class Mat>
- inline int
- choleskyDecomp(Mat &A, const char *UL)
- {
- assert(A.getCols() == A.getRows());
- lapack_int lpinfo = 0;
- lapack_int lrows = A.getRows();
- lapack_int ldl = A.getLd();
- dpotrf(UL, &lrows, A.getData(), &ldl, &lpinfo);
- int info = (int) lpinfo;
- return info;
- }
-
- // calc Cholesky Decomposition based solution X to A*X=B
- // for A pos. def. and symmetric supplied as uppper/lower triangle
- // packed in a vector if UPLO = 'U', AP(i + (j-1)*j/2) = A(i,j) for 1<=i<=j;
- // solutino X is returned in B and if B_in=I then B_out=X=inv(A)
- // A_out contains uupper or lower Cholesky decomposition
- template<class VecA, class MatB>
- inline int
- choleskySolver(VecA &A, MatB &B, const char *UL)
- {
- //assert(A.getCols() == A.getRows());
- lapack_int lpinfo = 0;
- lapack_int size = B.getRows();
- lapack_int bcols = B.getCols();
- lapack_int ldl = B.getLd();
- dppsv(UL, &size, &bcols, A.getData(), B.getData(), &ldl, &lpinfo);
- int info = (int) lpinfo;
- return info;
- }
-
-} // End of namespace
-
-#endif
diff --git a/mex/sources/estimation/libmat/Makefile.am b/mex/sources/estimation/libmat/Makefile.am
deleted file mode 100644
index b73cf569f90239361fb775c17f024ca00774416f..0000000000000000000000000000000000000000
--- a/mex/sources/estimation/libmat/Makefile.am
+++ /dev/null
@@ -1,22 +0,0 @@
-if HAVE_BLAS
-if HAVE_LAPACK
-SUBDIRS = tests
-endif
-endif
-
-EXTRA_DIST = \
- Matrix.hh \
- Matrix.cc \
- Vector.hh \
- Vector.cc \
- BlasBindings.hh \
- DiscLyapFast.hh \
- GeneralizedSchurDecomposition.cc \
- GeneralizedSchurDecomposition.hh \
- LapackBindings.hh \
- LUSolver.cc \
- LUSolver.hh \
- QRDecomposition.cc \
- QRDecomposition.hh \
- VDVEigDecomposition.cc \
- VDVEigDecomposition.hh
diff --git a/mex/sources/estimation/libmat/Matrix.cc b/mex/sources/estimation/libmat/Matrix.cc
deleted file mode 100644
index 9e0dffe157ad36227dd42e8e48bccaa315d16730..0000000000000000000000000000000000000000
--- a/mex/sources/estimation/libmat/Matrix.cc
+++ /dev/null
@@ -1,92 +0,0 @@
-/*
- * Copyright (C) 2010-2011 Dynare Team
- *
- * This file is part of Dynare.
- *
- * Dynare is free software: you can redistribute it and/or modify
- * it under the terms of the GNU General Public License as published by
- * the Free Software Foundation, either version 3 of the License, or
- * (at your option) any later version.
- *
- * Dynare is distributed in the hope that it will be useful,
- * but WITHOUT ANY WARRANTY; without even the implied warranty of
- * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
- * GNU General Public License for more details.
- *
- * You should have received a copy of the GNU General Public License
- * along with Dynare. If not, see <http://www.gnu.org/licenses/>.
- */
-
-#include "Matrix.hh"
-
-#include <cstring>
-#include <cassert>
-
-Matrix::Matrix(size_t rows_arg, size_t cols_arg) : rows(rows_arg), cols(cols_arg)
-{
- data = new double[rows*cols];
-}
-
-Matrix::Matrix(size_t size_arg) : rows(size_arg), cols(size_arg)
-{
- data = new double[rows*cols];
-}
-
-Matrix::Matrix(const Matrix &arg) : rows(arg.rows), cols(arg.cols)
-{
- data = new double[rows*cols];
- memcpy(data, arg.data, rows*cols*sizeof(double));
-}
-
-Matrix::~Matrix()
-{
- delete[] data;
-}
-
-Matrix &
-Matrix::operator=(const Matrix &arg)
-{
- assert(rows == arg.rows && cols == arg.cols);
- memcpy(data, arg.data, rows*cols*sizeof(double));
- return *this;
-}
-
-std::ostream &
-operator<<(std::ostream &out, const Matrix &M)
-{
- mat::print(out, M);
- return out;
-}
-
-MatrixView::MatrixView(double *data_arg, size_t rows_arg, size_t cols_arg, size_t ld_arg) :
- data(data_arg), rows(rows_arg), cols(cols_arg), ld(ld_arg)
-{
-}
-
-std::ostream &
-operator<<(std::ostream &out, const MatrixView &M)
-{
- mat::print(out, M);
- return out;
-}
-
-MatrixView &
-MatrixView::operator=(const MatrixView &arg)
-{
- assert(rows == arg.getRows() && cols == arg.getCols());
- for (size_t j = 0; j < cols; j++)
- memcpy(data + j*ld, arg.getData() + j*arg.getLd(), rows*sizeof(double));
- return *this;
-}
-
-MatrixConstView::MatrixConstView(const double *data_arg, size_t rows_arg, size_t cols_arg, size_t ld_arg) :
- data(data_arg), rows(rows_arg), cols(cols_arg), ld(ld_arg)
-{
-}
-
-std::ostream &
-operator<<(std::ostream &out, const MatrixConstView &M)
-{
- mat::print(out, M);
- return out;
-}
diff --git a/mex/sources/estimation/libmat/Matrix.hh b/mex/sources/estimation/libmat/Matrix.hh
deleted file mode 100644
index 860af9507e9d916e193ae8a62eb6aee0b65519ba..0000000000000000000000000000000000000000
--- a/mex/sources/estimation/libmat/Matrix.hh
+++ /dev/null
@@ -1,702 +0,0 @@
-/*
- * Copyright (C) 2010-2012 Dynare Team
- *
- * This file is part of Dynare.
- *
- * Dynare is free software: you can redistribute it and/or modify
- * it under the terms of the GNU General Public License as published by
- * the Free Software Foundation, either version 3 of the License, or
- * (at your option) any later version.
- *
- * Dynare is distributed in the hope that it will be useful,
- * but WITHOUT ANY WARRANTY; without even the implied warranty of
- * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
- * GNU General Public License for more details.
- *
- * You should have received a copy of the GNU General Public License
- * along with Dynare. If not, see <http://www.gnu.org/licenses/>.
- */
-
-#ifndef _MATRIX_HH
-#define _MATRIX_HH
-
-#include <algorithm>
-#include <iostream>
-#include <iomanip>
-
-#include <cstdlib>
-#include <cassert>
-#include <cstring>
-#include <cmath>
-#include <vector>
-
-#include "Vector.hh"
-
-/*
- This header defines three matrix classes, which implement a "matrix concept"
- (much like the concepts of the Standard Template Library or of Boost
- Library). The first class is a matrix owning the data space for its
- elements, and the other two are matrix "views" of another matrix, i.e. a
- contiguous submatrix. This design philosophy is close to the design of the
- GNU Scientific Library, but here using the syntactic power of C++ class and
- templates, while achieving very high efficiency.
-
- These classes can be used with various templated functions, including
- wrappers around the BLAS primitives.
-
- The expressions required to be valid for a class M implementing the "matrix concept" are:
- - M.getRows(): return number of rows
- - M.getCols(): return number of columns
- - M.getLd(): return the leading dimension (here the offset between two columns in the data space, since we are in column-major order)
- - M.getData(): return the pointer to the data space
- - M(i,j): get an element of the matrix
-
- The expressions required to be valid for a class M implementing the "mutable matrix concept" are (in addition to those of "matrix concept"):
- - M = X: assignment operator
- - M(i,j) = d: assign an element of the matrix
- - M.setAll(d): set all the elements of the matrix
-*/
-
-//! A full matrix, implements the "mutable matrix concept"
-/*! Owns the data space for the elements */
-class Matrix
-{
-private:
- //! Stored in column-major order, as in Fortran and MATLAB
- double *data;
- const size_t rows, cols;
-public:
- Matrix(size_t rows_arg, size_t cols_arg);
- Matrix(size_t size_arg);
- Matrix(const Matrix &arg);
- virtual ~Matrix();
- inline size_t getRows() const { return rows; }
- inline size_t getCols() const { return cols; }
- inline size_t getLd() const { return rows; }
- inline double *getData() { return data; }
- inline const double *getData() const { return data; }
- inline void setAll(double val) { std::fill_n(data, rows*cols, val); }
- inline double &operator() (size_t i, size_t j) { return data[i+j*rows]; }
- inline const double &operator() (size_t i, size_t j) const { return data[i+j*rows]; }
- //! Assignment operator, only works for matrices of same dimension
- template<class Mat>
- Matrix &
- operator= (const Mat &arg)
- {
- assert(rows == arg.getRows() && cols == arg.getCols());
- for (size_t j = 0; j < cols; j++)
- memcpy(data + j*rows, arg.getData() + j*arg.getLd(), rows*sizeof(double));
- return *this;
- }
- //! The copy assignment operator, which is not generated by the template assignment operator
- /*! See C++ standard, §12.8.9, in the footnote */
- Matrix &operator=(const Matrix &arg);
-};
-
-//! A contiguous submatrix of another matrix, implements the "mutable matrix concept"
-/*! Does not own the data space for the elements, so depends on another matrix */
-class MatrixView
-{
-private:
- double *const data;
- const size_t rows, cols, ld;
-public:
- MatrixView(double *data_arg, size_t rows_arg, size_t cols_arg, size_t ld_arg);
- template<class Mat>
- MatrixView(Mat &arg, size_t row_offset, size_t col_offset,
- size_t rows_arg, size_t cols_arg) :
- data(arg.getData() + row_offset + col_offset*arg.getLd()), rows(rows_arg), cols(cols_arg), ld(arg.getLd())
- {
- assert(row_offset < arg.getRows()
- && row_offset + rows_arg <= arg.getRows()
- && col_offset < arg.getCols()
- && col_offset + cols_arg <= arg.getCols());
- }
- virtual ~MatrixView(){};
- inline size_t getRows() const { return rows; }
- inline size_t getCols() const { return cols; }
- inline size_t getLd() const { return ld; }
- inline double *getData() { return data; }
- inline const double *getData() const { return data; }
- inline void setAll(double val)
- {
- for (double *p = data; p < data + cols*ld; p += ld)
- std::fill_n(p, rows, val);
- }
- inline double &operator() (size_t i, size_t j) { return data[i+j*ld]; }
- inline const double &operator() (size_t i, size_t j) const { return data[i+j*ld]; }
- //! Assignment operator, only works for matrices of same dimension
- template<class Mat>
- MatrixView &
- operator= (const Mat &arg)
- {
- assert(rows == arg.getRows() && cols == arg.getCols());
- for (size_t j = 0; j < cols; j++)
- memcpy(data + j*ld, arg.getData() + j*arg.getLd(), rows*sizeof(double));
- return *this;
- }
- //! The copy assignment operator, which is not generated by the template assignment operator
- /*! See C++ standard, §12.8.9, in the footnote */
- MatrixView &operator=(const MatrixView &arg);
-};
-
-//! Like MatrixView, but cannot be modified (implements the "matrix concept")
-class MatrixConstView
-{
-private:
- const double *const data;
- const size_t rows, cols, ld;
-public:
- MatrixConstView(const double *data_arg, size_t rows_arg, size_t cols_arg, size_t ld_arg);
- template<class Mat>
- MatrixConstView(const Mat &arg, size_t row_offset, size_t col_offset,
- size_t rows_arg, size_t cols_arg) :
- data(arg.getData() + row_offset + col_offset*arg.getLd()), rows(rows_arg), cols(cols_arg), ld(arg.getLd())
- {
- assert(row_offset < arg.getRows()
- && row_offset + rows_arg <= arg.getRows()
- && col_offset < arg.getCols()
- && col_offset + cols_arg <= arg.getCols());
- }
- virtual ~MatrixConstView(){};
- inline size_t getRows() const { return rows; }
- inline size_t getCols() const { return cols; }
- inline size_t getLd() const { return ld; }
- inline const double *getData() const { return data; }
- inline const double &operator() (size_t i, size_t j) const { return data[i+j*ld]; }
-};
-
-std::ostream &operator<<(std::ostream &out, const Matrix &M);
-std::ostream &operator<<(std::ostream &out, const MatrixView &M);
-std::ostream &operator<<(std::ostream &out, const MatrixConstView &M);
-
-namespace mat
-{
- //define nullVec (const vector<int>(0)) for assign and order by vector
- // It is used as a proxy for the ":" matlab operator:
- // i.e. zero sized int vector, nullVec, is interpreted as if one supplied ":"
- const std::vector<size_t> nullVec(0);
-
- template<class Mat>
- void
- print(std::ostream &out, const Mat &M)
- {
- for (size_t i = 0; i < M.getRows(); i++)
- {
- for (size_t j = 0; j < M.getCols(); j++)
- out << std::setw(13) << std::right << M(i, j) << " ";
- out << std::endl;
- }
- }
-
- template<class Mat>
- inline VectorView
- get_col(Mat &M, size_t j)
- {
- return VectorView(M.getData()+j*M.getLd(), M.getRows(), 1);
- }
-
- template<class Mat>
- inline VectorView
- get_row(Mat &M, size_t i)
- {
- return VectorView(M.getData()+i, M.getCols(), M.getLd());
- }
-
- template<class Mat>
- inline VectorConstView
- get_col(const Mat &M, size_t j)
- {
- return VectorConstView(M.getData()+j*M.getLd(), M.getRows(), 1);
- }
-
- template<class Mat>
- inline VectorConstView
- get_row(const Mat &M, size_t i)
- {
- return VectorConstView(M.getData()+i, M.getCols(), M.getLd());
- }
-
- template<class Mat1, class Mat2>
- inline void
- col_copy(const Mat1 &src, size_t col_src, Mat2 &dest, size_t col_dest)
- {
- assert(src.getRows() == dest.getRows()
- && col_src < src.getCols() && col_dest < dest.getCols());
- memcpy(dest.getData() + col_dest*dest.getLd(),
- const_cast<double *>(src.getData()) + col_src*src.getLd(),
- src.getRows()*sizeof(double));
- }
-
- template<class Mat1, class Mat2>
- inline void
- col_copy(const Mat1 &src, size_t col_src, size_t row_offset_src, size_t row_nb,
- Mat2 &dest, size_t col_dest, size_t row_offset_dest)
- {
- assert(col_src < src.getCols() && col_dest < dest.getCols()
- && row_offset_src < src.getRows() && row_offset_src+row_nb <= src.getRows()
- && row_offset_dest < dest.getRows() && row_offset_dest+row_nb <= dest.getRows());
- memcpy(dest.getData() + row_offset_dest + col_dest*dest.getLd(),
- src.getData() + row_offset_src + col_src*src.getLd(),
- row_nb*sizeof(double));
- }
-
- template<class Mat1, class Mat2>
- inline void
- row_copy(const Mat1 &src, size_t row_src, Mat2 &dest, size_t row_dest)
- {
- assert(src.getCols() == dest.getCols()
- && row_src < src.getRows() && row_dest < dest.getRows());
- const double *p1 = src.getData() + row_src;
- double *p2 = dest.getData() + row_dest;
- while (p1 < src.getData() + src.getCols() * src.getLd())
- {
- *p2 = *p1;
- p1 += src.getLd();
- p2 += dest.getLd();
- }
- }
-
- template<class Mat>
- inline void
- col_set(Mat &M, size_t col, size_t row_offset, size_t row_nb, double val)
- {
- assert(col < M.getCols());
- assert(row_offset < M.getRows() && row_offset + row_nb <= M.getRows());
- std::fill_n(M.getData() + M.getLd()*col + row_offset, row_nb, val);
- }
-
- //! Copy under the diagonal the elements above the diagonal
- template<class Mat>
- inline void
- copy_upper_to_lower(Mat &M)
- {
- size_t d = std::min(M.getCols(), M.getRows());
- for (size_t i = 0; i < d; i++)
- for (size_t j = 0; j < i; j++)
- M(i, j) = M(j, i);
- }
-
- //! Copy above the diagonal the elements under the diagonal
- template<class Mat>
- inline void
- copy_lower_to_upper(Mat &M)
- {
- size_t d = std::min(M.getCols(), M.getRows());
- for (size_t i = 0; i < d; i++)
- for (size_t j = 0; j < i; j++)
- M(j, i) = M(i, j);
- }
-
- //! Fill the matrix with the identity matrix
- template<class Mat>
- inline void
- set_identity(Mat &M)
- {
- M.setAll(0.0);
- size_t d = std::min(M.getCols(), M.getRows());
- for (size_t i = 0; i < d; i++)
- M(i, i) = 1.0;
- }
-
- //! In-place transpose of a square matrix
- template<class Mat>
- inline void
- transpose(Mat &M)
- {
- assert(M.getRows() == M.getCols());
- for (size_t i = 0; i < M.getRows(); i++)
- for (size_t j = 0; j < i; j++)
- std::swap(M(i, j), M(j, i));
- }
-
- //! Computes M1 = M2' (even for rectangular matrices)
- template<class Mat1, class Mat2>
- inline void
- transpose(Mat1 &M1, const Mat2 &M2)
- {
- assert(M1.getRows() == M2.getCols() && M1.getCols() == M2.getRows());
- for (size_t i = 0; i < M1.getRows(); i++)
- for (size_t j = 0; j < M1.getCols(); j++)
- M1(i, j) = M2(j, i);
- }
-
- //! Computes m1 = m1 + m2
- template<class Mat1, class Mat2>
- void
- add(Mat1 &m1, const Mat2 &m2)
- {
- assert(m1.getRows() == m2.getRows() && m1.getCols() == m2.getCols());
- double *p1 = m1.getData();
- const double *p2 = m2.getData();
- while (p1 < m1.getData() + m1.getCols() * m1.getLd())
- {
- double *pp1 = p1;
- const double *pp2 = p2;
- while (pp1 < p1 + m1.getRows())
- *pp1++ += *pp2++;
-
- p1 += m1.getLd();
- p2 += m2.getLd();
- }
- }
-
- //! Computes m1 = m1 + number
- template<class Mat1>
- void
- add(Mat1 &m1, double d)
- {
- double *p1 = m1.getData();
-
- while (p1 < m1.getData() + m1.getCols() * m1.getLd())
- {
- double *pp1 = p1;
- while (pp1 < p1 + m1.getRows())
- *pp1++ += d;
-
- p1 += m1.getLd();
- }
- }
-
- //! Computes m1 = m1 - m2
- template<class Mat1, class Mat2>
- void
- sub(Mat1 &m1, const Mat2 &m2)
- {
- assert(m1.getRows() == m2.getRows() && m1.getCols() == m2.getCols());
- double *p1 = m1.getData();
- const double *p2 = m2.getData();
- while (p1 < m1.getData() + m1.getCols() * m1.getLd())
- {
- double *pp1 = p1;
- const double *pp2 = p2;
- while (pp1 < p1 + m1.getRows())
- *pp1++ -= *pp2++;
-
- p1 += m1.getLd();
- p2 += m2.getLd();
- }
- }
-
- //! Computes m1 = m1 - number
- template<class Mat1>
- void
- sub(Mat1 &m1, double d)
- {
- add(m1, -1.0*d);
- }
-
- //! Does m = -m
- template<class Mat>
- void
- negate(Mat &m)
- {
- double *p = m.getData();
- while (p < m.getData() + m.getCols() * m.getLd())
- {
- double *pp = p;
- while (pp < p + m.getRows())
- {
- *pp = -*pp;
- pp++;
- }
-
- p += m.getLd();
- }
- }
-
- // Computes the infinite norm of a matrix
- template<class Mat>
- double
- nrminf(const Mat &m)
- {
- double nrm = 0;
- const double *p = m.getData();
- while (p < m.getData() + m.getCols() * m.getLd())
- {
- const double *pp = p;
- while (pp < p + m.getRows())
- {
- if (fabs(*pp) > nrm)
- nrm = fabs(*pp);
- pp++;
- }
-
- p += m.getLd();
- }
- return nrm;
- }
-
- // emulates Matlab command A(:,b)=B(:,d) where b,d are size_t vectors or nullVec as a proxy for ":")
- // i.e. zero sized vector (or mat::nullVec) is interpreted as if one supplied ":" in matlab
- template<class Mat1, class Mat2>
- void
- reorderColumnsByVectors(Mat1 &a, const std::vector<size_t> &vToCols,
- const Mat2 &b, const std::vector<size_t> &vcols)
- {
- size_t ncols = 0, toncols = 0;
- const std::vector<size_t> *vpToCols = 0, *vpCols = 0;
- std::vector<size_t> tmpvpToCols(0), tmpvpCols(0);
- assert(b.getRows() == a.getRows());
-
- if (vToCols.size() == 0 && vcols.size() == 0)
- a = b;
- else
- {
- if (vToCols.size() == 0)
- {
- toncols = a.getCols();
- tmpvpToCols.reserve(toncols);
- for (size_t i = 0; i < toncols; ++i)
- tmpvpToCols[i] = i;
- vpToCols = (const std::vector<size_t> *)&tmpvpToCols;
- }
- else
- {
- for (size_t i = 0; i < vToCols.size(); ++i)
- {
- assert(vToCols[i] < a.getCols()); //Negative or too large indices
- toncols++;
- }
- assert(toncols <= a.getCols()); // check wrong dimensions for assignment by vector
- vpToCols = &vToCols;
- }
-
- if (vcols.size() == 0)
- {
- ncols = b.getCols();
- tmpvpCols.reserve(ncols);
- for (size_t i = 0; i < ncols; ++i)
- tmpvpCols[i] = i;
- vpCols = (const std::vector<size_t> *)&tmpvpCols;
- }
- else
- {
- for (size_t i = 0; i < vcols.size(); ++i)
- {
- assert(vcols[i] < b.getCols()); //Negative or too large indices
- ncols++;
- }
- assert(ncols <= b.getCols()); // check wrong dimensions for assignment by vector
- vpCols = &vcols;
- }
-
- assert(toncols == ncols && ncols > 0);
- for (size_t j = 0; j < ncols; ++j)
- col_copy(b, (*vpCols)[j], a, (*vpToCols)[j]);
- }
- }
-
- // emulates Matlab command A(a,:)=B(c,:) where a,c are size_t vectors or nullVec as a proxy for ":")
- // i.e. zero sized vector (or mat::nullVec) is interpreted as if one supplied ":" in matlab
- template<class Mat1, class Mat2>
- void
- reorderRowsByVectors(Mat1 &a, const std::vector<size_t> &vToRows,
- const Mat2 &b, const std::vector<size_t> &vrows)
- {
- size_t nrows = 0, tonrows = 0;
- const std::vector<size_t> *vpToRows = 0, *vpRows = 0;
- std::vector<size_t> tmpvpToRows(0), tmpvpRows(0);
-
- //assert(b.getRows() >= a.getRows() && b.getCols() == a.getCols());
- assert(b.getCols() == a.getCols());
- if (vToRows.size() == 0 && vrows.size() == 0)
- a = b;
- else
- {
- if (vToRows.size() == 0)
- {
- tonrows = a.getRows();
- tmpvpToRows.reserve(tonrows);
- for (size_t i = 0; i < tonrows; ++i)
- tmpvpToRows[i] = i;
- vpToRows = (const std::vector<size_t> *)&tmpvpToRows;
- }
- else
- {
- for (size_t i = 0; i < vToRows.size(); ++i)
- {
- assert(vToRows[i] < a.getRows()); //Negative or too large indices
- tonrows++;
- }
- assert(tonrows <= a.getRows()); // check wrong dimensions for assignment by vector
- vpToRows = &vToRows;
- }
-
- if (vrows.size() == 0)
- {
- nrows = b.getRows();
- tmpvpRows.reserve(nrows);
- for (size_t i = 0; i < nrows; ++i)
- tmpvpRows[i] = i;
- vpRows = (const std::vector<size_t> *)&tmpvpRows;
- }
- else
- {
- for (size_t i = 0; i < vrows.size(); ++i)
- {
- assert(vrows[i] < b.getRows()); //Negative or too large indices
- nrows++;
- }
- assert(nrows <= b.getRows()); // check wrong dimensions for assignment by vector
- vpRows = &vrows;
- }
-
- assert(tonrows == nrows && nrows > 0);
- for (size_t i = 0; i < nrows; ++i)
- row_copy(b, (*vpRows)[i], a, (*vpToRows)[i]);
- }
- }
-
- // emulates Matlab command A(a,b)=B(c,d) where a,b,c,d are size_t vectors or nullVec as a proxy for ":")
- // i.e. zero sized vector (or mat::nullVec) is interpreted as if one supplied ":" in matlab
- template<class Mat1, class Mat2>
- void
- assignByVectors(Mat1 &a, const std::vector<size_t> &vToRows, const std::vector<size_t> &vToCols,
- const Mat2 &b, const std::vector<size_t> &vrows, const std::vector<size_t> &vcols)
- {
- size_t nrows = 0, ncols = 0, tonrows = 0, toncols = 0;
- const std::vector<size_t> *vpToCols = 0, *vpToRows = 0, *vpRows = 0, *vpCols = 0;
- std::vector<size_t> tmpvpToCols(0), tmpvpToRows(0), tmpvpRows(0), tmpvpCols(0);
-
- if (vToRows.size() == 0 && vToCols.size() == 0 && vrows.size() == 0 && vcols.size() == 0)
- a = b;
- else if (vToRows.size() == 0 && vrows.size() == 0) // just reorder columns
- reorderColumnsByVectors(a, vToCols, b, vcols);
- else if (vToCols.size() == 0 && vcols.size() == 0) // just reorder rows
- reorderRowsByVectors(a, vToRows, b, vrows);
- else
- {
- if (vToRows.size() == 0)
- {
- tonrows = a.getRows();
- tmpvpToRows.reserve(tonrows);
- for (size_t i = 0; i < tonrows; ++i)
- tmpvpToRows[i] = i;
- vpToRows = (const std::vector<size_t> *)&tmpvpToRows;
- }
- else
- {
- for (size_t i = 0; i < vToRows.size(); ++i)
- {
- assert(vToRows[i] < a.getRows()); //Negative or too large indices
- tonrows++;
- }
- assert(tonrows <= a.getRows()); // check wrong dimensions for assignment by vector
- vpToRows = &vToRows;
- }
-
- if (vToCols.size() == 0)
- {
- toncols = a.getCols();
- tmpvpToCols.reserve(toncols);
- for (size_t i = 0; i < toncols; ++i)
- tmpvpToCols[i] = i;
- vpToCols = (const std::vector<size_t> *)&tmpvpToCols;
- }
- else
- {
- for (size_t i = 0; i < vToCols.size(); ++i)
- {
- assert(vToCols[i] < a.getCols()); //Negative or too large indices
- toncols++;
- }
- assert(toncols <= a.getCols()); // check wrong dimensions for assignment by vector
- vpToCols = &vToCols;
- }
-
- if (vrows.size() == 0)
- {
- nrows = b.getRows();
- tmpvpRows.reserve(nrows);
- for (size_t i = 0; i < nrows; ++i)
- tmpvpRows[i] = i;
- vpRows = (const std::vector<size_t> *)&tmpvpRows;
- }
- else
- {
- for (size_t i = 0; i < vrows.size(); ++i)
- {
- assert(vrows[i] < b.getRows()); //Negative or too large indices
- nrows++;
- }
- assert(nrows <= b.getRows()); // check wrong dimensions for assignment by vector
- vpRows = &vrows;
- }
-
- if (vcols.size() == 0)
- {
- ncols = b.getCols();
- tmpvpCols.reserve(ncols);
- for (size_t i = 0; i < ncols; ++i)
- tmpvpCols[i] = i;
- vpCols = (const std::vector<size_t> *)&tmpvpCols;
- }
- else
- {
- for (size_t i = 0; i < vcols.size(); ++i)
- {
- assert(vcols[i] < b.getCols()); //Negative or too large indices
- ncols++;
- }
- assert(ncols <= b.getCols()); // check wrong dimensions for assignment by vector
- vpCols = &vcols;
- }
-
- assert(tonrows == nrows && toncols == ncols && nrows * ncols > 0);
- for (size_t i = 0; i < nrows; ++i)
- for (size_t j = 0; j < ncols; ++j)
- a((*vpToRows)[i], (*vpToCols)[j]) = b((*vpRows)[i], (*vpCols)[j]);
- }
- }
-
- //emulates Matlab repmat: Mat2 = multv*multh tiled [Mat1]
- template<class Mat1, class Mat2 >
- void
- repmat(Mat1 &a, size_t multv, size_t multh, Mat2 &repMat) // vertical and horisontal replicators
- {
- assert(repMat.getRows() == multv * a.getRows() && repMat.getCols() == multh * a.getCols());
- for (size_t i = 0; i < multv; ++i)
- for (size_t j = 0; j < multh; ++j)
- for (size_t k = 0; k < a.getCols(); ++k)
- col_copy(a, k, 0, a.getRows(), repMat, a.getCols() * j + k, a.getRows() * i);
- };
-
- template<class Mat1, class Mat2>
- bool
- isDiff(const Mat1 &m1, const Mat2 &m2, const double tol = 0.0)
- {
- assert(m2.getRows() == m1.getRows() && m2.getCols() == m1.getCols());
- const double *p1 = m1.getData();
- const double *p2 = m2.getData();
- while (p1 < m1.getData() + m1.getCols() * m1.getLd())
- {
- const double *pp1 = p1;
- const double *pp2 = p2;
- while (pp1 < p1 + m1.getRows())
- if (fabs(*pp1++ - *pp2++) > tol)
- return true;
-
- p1 += m1.getLd();
- p2 += m2.getLd();
- }
- return false;
- }
-
- //traverse the upper triangle only along diagonals where higher changes occur
- template<class Mat1, class Mat2>
- bool
- isDiffSym(const Mat1 &m1, const Mat2 &m2, const double tol = 0.0)
- {
- assert(m2.getRows() == m1.getRows() && m2.getCols() == m1.getCols()
- && m2.getRows() == m1.getCols() && m2.getCols() == m1.getRows());
- for (size_t i = 0; i < m1.getCols(); i++)
- for (size_t j = 0; i + j < m1.getCols(); j++)
- if (fabs(m1(j, j + i) - m2(j, j + i)) > tol)
- return true;
- return false;
- }
-
-} // End of namespace
-
-#endif
diff --git a/mex/sources/estimation/libmat/QRDecomposition.cc b/mex/sources/estimation/libmat/QRDecomposition.cc
deleted file mode 100644
index 38e3a5f5718a90d667fa6b6356be34ef85d1eb77..0000000000000000000000000000000000000000
--- a/mex/sources/estimation/libmat/QRDecomposition.cc
+++ /dev/null
@@ -1,39 +0,0 @@
-/*
- * Copyright (C) 2010 Dynare Team
- *
- * This file is part of Dynare.
- *
- * Dynare is free software: you can redistribute it and/or modify
- * it under the terms of the GNU General Public License as published by
- * the Free Software Foundation, either version 3 of the License, or
- * (at your option) any later version.
- *
- * Dynare is distributed in the hope that it will be useful,
- * but WITHOUT ANY WARRANTY; without even the implied warranty of
- * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
- * GNU General Public License for more details.
- *
- * You should have received a copy of the GNU General Public License
- * along with Dynare. If not, see <http://www.gnu.org/licenses/>.
- */
-
-#include <algorithm> // For std::min
-
-#include "QRDecomposition.hh"
-
-QRDecomposition::QRDecomposition(size_t rows_arg, size_t cols_arg, size_t cols2_arg) :
- rows(rows_arg), cols(cols_arg), mind(std::min(rows, cols)), cols2(cols2_arg),
- lwork(rows*cols), lwork2(cols2)
-{
- work = new double[lwork];
- work2 = new double[lwork2];
-
- tau = new double[mind];
-}
-
-QRDecomposition::~QRDecomposition()
-{
- delete[] work;
- delete[] work2;
- delete[] tau;
-}
diff --git a/mex/sources/estimation/libmat/QRDecomposition.hh b/mex/sources/estimation/libmat/QRDecomposition.hh
deleted file mode 100644
index d8022a7e5cc66d60fd971f9865a3345b6021081f..0000000000000000000000000000000000000000
--- a/mex/sources/estimation/libmat/QRDecomposition.hh
+++ /dev/null
@@ -1,72 +0,0 @@
-/*
- * Copyright (C) 2010-2011 Dynare Team
- *
- * This file is part of Dynare.
- *
- * Dynare is free software: you can redistribute it and/or modify
- * it under the terms of the GNU General Public License as published by
- * the Free Software Foundation, either version 3 of the License, or
- * (at your option) any later version.
- *
- * Dynare is distributed in the hope that it will be useful,
- * but WITHOUT ANY WARRANTY; without even the implied warranty of
- * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
- * GNU General Public License for more details.
- *
- * You should have received a copy of the GNU General Public License
- * along with Dynare. If not, see <http://www.gnu.org/licenses/>.
- */
-
-#include <algorithm> // For std::min()
-
-#include <dynlapack.h>
-
-#include "Vector.hh"
-#include "Matrix.hh"
-#include "BlasBindings.hh"
-
-class QRDecomposition
-{
-private:
- const size_t rows, cols, mind;
- //! Number of columns of the matrix to be left-multiplied by Q
- const size_t cols2;
- lapack_int lwork, lwork2;
- double *work, *work2, *tau;
-public:
- /*!
- \todo Replace heuristic choice for workspace size by a query to determine the optimal size
- \param[in] rows_arg Number of rows of the matrix to decompose
- \param[in] cols_arg Number of columns of the matrix to decompose
- \param[in] cols2_arg Number of columns of the matrix to be multiplied by Q
- */
- QRDecomposition(size_t rows_arg, size_t cols_arg, size_t cols2_arg);
- virtual ~QRDecomposition();
- //! Performs the QR decomposition of a matrix, and left-multiplies another matrix by Q
- /*!
- \param[in,out] A On input, the matrix to be decomposed. On output, equals to the output of dgeqrf
- \param[in] trans Specifies whether Q should be transposed before the multiplication, either "T" or "N"
- \param[in,out] C The matrix to be left-multiplied by Q, modified in place
- */
- template<class Mat1, class Mat2>
- void computeAndLeftMultByQ(Mat1 &A, const char *trans, Mat2 &C);
-};
-
-template<class Mat1, class Mat2>
-void
-QRDecomposition::computeAndLeftMultByQ(Mat1 &A, const char *trans, Mat2 &C)
-{
- assert(A.getRows() == rows && A.getCols() == cols);
- assert(C.getRows() == rows && C.getCols() == cols2);
-
- lapack_int m = rows, n = cols, lda = A.getLd();
- lapack_int info;
- dgeqrf(&m, &n, A.getData(), &lda, tau, work, &lwork, &info);
- assert(info == 0);
-
- n = cols2;
- lapack_int k = mind, ldc = C.getLd();
- dormqr("L", trans, &m, &n, &k, A.getData(), &lda, tau, C.getData(), &ldc,
- work2, &lwork2, &info);
- assert(info == 0);
-}
diff --git a/mex/sources/estimation/libmat/VDVEigDecomposition.cc b/mex/sources/estimation/libmat/VDVEigDecomposition.cc
deleted file mode 100644
index 7e32bb094e1747f173ade18ec866a5019cd7b894..0000000000000000000000000000000000000000
--- a/mex/sources/estimation/libmat/VDVEigDecomposition.cc
+++ /dev/null
@@ -1,49 +0,0 @@
-/*
- * Copyright (C) 2010-2011 Dynare Team
- *
- * This file is part of Dynare.
- *
- * Dynare is free software: you can redistribute it and/or modify
- * it under the terms of the GNU General Public License as published by
- * the Free Software Foundation, either version 3 of the License, or
- * (at your option) any later version.
- *
- * Dynare is distributed in the hope that it will be useful,
- * but WITHOUT ANY WARRANTY; without even the implied warranty of
- * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
- * GNU General Public License for more details.
- *
- * You should have received a copy of the GNU General Public License
- * along with Dynare. If not, see <http://www.gnu.org/licenses/>.
- */
-
-#include "VDVEigDecomposition.hh"
-
-VDVEigDecomposition::VDVEigDecomposition(const Matrix &m) throw (VDVEigException) :
- lda(m.getLd()), n(m.getCols()), lwork(-1),
- info(0), converged(false), V(m), D(n)
-{
- if (m.getRows() != m.getCols())
- throw (VDVEigException(info, "Matrix is not square in VDVEigDecomposition constructor"));
-
- double tmpwork;
- dsyev("V", "U", &n, V.getData(), &lda, D.getData(), &tmpwork, &lwork, &info);
- lwork = (lapack_int) tmpwork;
- work = new double[lwork];
- if (info < 0)
- throw (VDVEigException(info, "Internal error in VDVEigDecomposition constructor"));
-}
-
-VDVEigDecomposition::VDVEigDecomposition(size_t inn) throw (VDVEigException) :
- lda(inn), n(inn), lwork(3*inn-1),
- info(0), converged(false), V(inn), D(inn)
-{
- work = new double[lwork];
-};
-
-std::ostream &
-operator<<(std::ostream &out, const VDVEigDecomposition::VDVEigException &e)
-{
- out << " info " << e.info << ": " << e.message << "\n";
- return out;
-}
diff --git a/mex/sources/estimation/libmat/VDVEigDecomposition.hh b/mex/sources/estimation/libmat/VDVEigDecomposition.hh
deleted file mode 100644
index d717485302f002532c45e03790f93553c0f6e112..0000000000000000000000000000000000000000
--- a/mex/sources/estimation/libmat/VDVEigDecomposition.hh
+++ /dev/null
@@ -1,125 +0,0 @@
-/*
- * Copyright (C) 2010-2011 Dynare Team
- *
- * This file is part of Dynare.
- *
- * Dynare is free software: you can redistribute it and/or modify
- * it under the terms of the GNU General Public License as published by
- * the Free Software Foundation, either version 3 of the License, or
- * (at your option) any later version.
- *
- * Dynare is distributed in the hope that it will be useful,
- * but WITHOUT ANY WARRANTY; without even the implied warranty of
- * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
- * GNU General Public License for more details.
- *
- * You should have received a copy of the GNU General Public License
- * along with Dynare. If not, see <http://www.gnu.org/licenses/>.
- */
-
-/**
- * Calculates vector of Eigen values D and matrix of Eigen vectors V
- * of input matrix m
- */
-
-#if !defined(VDVEigDec_INCLUDE)
-#define VDVEigDec_INCLUDE
-
-#include <cstdlib>
-#include "Vector.hh"
-#include "Matrix.hh"
-#include <dynlapack.h>
-
-class VDVEigDecomposition
-{
- lapack_int lda, n;
- lapack_int lwork, info;
- double *work;
- bool converged;
- Matrix V;
- Vector D;
-public:
-
-public:
- class VDVEigException
- {
- public:
- const lapack_int info;
- std::string message;
- VDVEigException(lapack_int info_arg, std::string message_arg) :
- info(info_arg), message(message_arg)
- {
- };
- };
-
- /**
- * This constructor only creates optimal workspace using
- * input matrix m
- */
- VDVEigDecomposition(const Matrix &m) throw (VDVEigException);
-
- /**
- * This constructoro only crates workspace using the size of
- * the input matrix m
- */
- VDVEigDecomposition(size_t n) throw (VDVEigException);
-
- virtual ~VDVEigDecomposition()
- {
- delete[] work;
- };
- template <class Mat>
- void calculate(const Mat &H) throw (VDVEigException);
- // get eigenvalues
- Vector &
- getD()
- {
- return D;
- };
- // get eigen vector
- Matrix &
- getV()
- {
- return V;
- };
- // check if converged
- bool
- hasConverged()
- {
- return converged;
- };
-};
-
-template <class Mat>
-void
-VDVEigDecomposition::calculate(const Mat &m) throw (VDVEigException)
-{
- info = 0;
- if (m.getRows() != m.getCols())
- throw (VDVEigException(info, "Matrix is not square in VDVEigDecomposition calculate"));
-
- if (m.getCols() != (size_t) n || m.getLd() != (size_t) lda)
- throw (VDVEigException(info, "Matrix not matching VDVEigDecomposition class"));
-
- double tmpwork;
- lapack_int tmplwork = -1;
- V = m;
- dsyev("V", "U", &n, V.getData(), &lda, D.getData(), &tmpwork, &tmplwork, &info);
- if (lwork < (lapack_int) tmpwork)
- {
- lwork = (lapack_int) tmpwork;
- delete[] work;
- work = new double[lwork];
- }
- dsyev("V", "U", &n, V.getData(), &lda, D.getData(), work, &lwork, &info);
-
- if (info < 0)
- throw (VDVEigException(info, "Internal error in VDVEigDecomposition calculation"));
- converged = true;
- if (info)
- converged = false;
-}
-
-std::ostream &operator<<(std::ostream &out, const VDVEigDecomposition::VDVEigException &e);
-
-#endif
diff --git a/mex/sources/estimation/libmat/Vector.cc b/mex/sources/estimation/libmat/Vector.cc
deleted file mode 100644
index 3d16039981fc0c6d38f56a5d378302d306dfa455..0000000000000000000000000000000000000000
--- a/mex/sources/estimation/libmat/Vector.cc
+++ /dev/null
@@ -1,119 +0,0 @@
-/*
- * Copyright (C) 2010-2011 Dynare Team
- *
- * This file is part of Dynare.
- *
- * Dynare is free software: you can redistribute it and/or modify
- * it under the terms of the GNU General Public License as published by
- * the Free Software Foundation, either version 3 of the License, or
- * (at your option) any later version.
- *
- * Dynare is distributed in the hope that it will be useful,
- * but WITHOUT ANY WARRANTY; without even the implied warranty of
- * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
- * GNU General Public License for more details.
- *
- * You should have received a copy of the GNU General Public License
- * along with Dynare. If not, see <http://www.gnu.org/licenses/>.
- */
-
-#include "Vector.hh"
-
-#include <cstring>
-#include <cassert>
-
-Vector::Vector(size_t size_arg) : size(size_arg)
-{
- data = new double[size];
-}
-
-Vector::Vector(const Vector &arg) : size(arg.size)
-{
- data = new double[size];
- memcpy(data, arg.data, size*sizeof(double));
-}
-
-Vector::~Vector()
-{
- delete[] data;
-}
-
-Vector &
-Vector::operator=(const Vector &arg)
-{
- assert(size == arg.size);
- memcpy(data, arg.data, size*sizeof(double));
- return *this;
-}
-
-std::ostream &
-operator<<(std::ostream &out, const Vector &V)
-{
- vec::print(out, V);
- return out;
-}
-
-VectorView::VectorView(double *data_arg, size_t size_arg, size_t stride_arg) :
- data(data_arg), size(size_arg), stride(stride_arg)
-{
-}
-
-VectorView::VectorView(Vector &arg, size_t offset, size_t size_arg) :
- data(arg.getData() + offset*arg.getStride()), size(size_arg), stride(arg.getStride())
-{
- assert(offset < arg.getSize() && offset + size <= arg.getSize());
-}
-
-VectorView::VectorView(VectorView &arg, size_t offset, size_t size_arg) :
- data(arg.getData() + offset*arg.getStride()), size(size_arg), stride(arg.getStride())
-{
- assert(offset < arg.getSize() && offset + size <= arg.getSize());
-}
-
-VectorView &
-VectorView::operator=(const VectorView &arg)
-{
- assert(size == arg.getSize());
- double *p1;
- const double *p2;
- for (p1 = data, p2 = arg.getData(); p1 < data + size*stride; p1 += stride, p2 += arg.getStride())
- *p1 = *p2;
- return *this;
-}
-
-VectorConstView::VectorConstView(const double *data_arg, size_t size_arg, size_t stride_arg) :
- data(data_arg), size(size_arg), stride(stride_arg)
-{
-}
-
-VectorConstView::VectorConstView(const Vector &arg, size_t offset, size_t size_arg) :
- data(arg.getData() + offset*arg.getStride()), size(size_arg), stride(arg.getStride())
-{
- assert(offset < arg.getSize() && offset + size <= arg.getSize());
-}
-
-VectorConstView::VectorConstView(const VectorView &arg, size_t offset, size_t size_arg) :
- data(arg.getData() + offset*arg.getStride()), size(size_arg), stride(arg.getStride())
-{
- assert(offset < arg.getSize() && offset + size <= arg.getSize());
-}
-
-VectorConstView::VectorConstView(const VectorConstView &arg, size_t offset, size_t size_arg) :
- data(arg.getData() + offset*arg.getStride()), size(size_arg), stride(arg.getStride())
-{
- assert(offset < arg.getSize() && offset + size <= arg.getSize());
-}
-
-std::ostream &
-operator<<(std::ostream &out, const VectorView &V)
-{
- vec::print(out, V);
- return out;
-}
-
-std::ostream &
-operator<<(std::ostream &out, const VectorConstView &V)
-{
- vec::print(out, V);
- return out;
-}
diff --git a/mex/sources/estimation/libmat/Vector.hh b/mex/sources/estimation/libmat/Vector.hh
deleted file mode 100644
index d020beaf4664698f0cbeca6aa158ca56921be9fd..0000000000000000000000000000000000000000
--- a/mex/sources/estimation/libmat/Vector.hh
+++ /dev/null
@@ -1,253 +0,0 @@
-/*
- * Copyright (C) 2010-2011 Dynare Team
- *
- * This file is part of Dynare.
- *
- * Dynare is free software: you can redistribute it and/or modify
- * it under the terms of the GNU General Public License as published by
- * the Free Software Foundation, either version 3 of the License, or
- * (at your option) any later version.
- *
- * Dynare is distributed in the hope that it will be useful,
- * but WITHOUT ANY WARRANTY; without even the implied warranty of
- * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
- * GNU General Public License for more details.
- *
- * You should have received a copy of the GNU General Public License
- * along with Dynare. If not, see <http://www.gnu.org/licenses/>.
- */
-
-#ifndef _VECTOR_HH
-#define _VECTOR_HH
-
-#include <algorithm>
-#include <iostream>
-
-#include <cstdlib>
-#include <cassert>
-#include <cmath>
-
-/*
- This header defines three vector classes, which implement a "vector concept"
- (much like the concepts of the Standard Template Library or of Boost
- Library). The first class is a vector owning the data space for its elements,
- and the other two are vector "views" of something else (either a subvector of
- another vector, or a row or column of a matrix). This design philosophy is
- close to the design of the GNU Scientific Library, but here using the
- syntactic power of C++ class and templates, while achieving very high
- efficiency.
-
- These classes can be used with various templated functions, including
- wrappers around the BLAS primitives.
-
- The expressions required to be valid for a class V implementing the "vector concept" are:
- - V.getSize(): return number of elements
- - V.getStride(): return the stride, i.e. the offset between two elements in the data space
- - V.getData(): return the pointer to the data space
- - V(i): get an element of the vector
-
- The expressions required to be valid for a class V implementing the "mutable vector concept" are (in addition to those of "vector concept"):
- - V = X: assignment operator
- - V(i) = d: assign an element of the vector
- - V.setAll(d): set all the elements of the vector
-
-*/
-
-//! A full vector, implements the "mutable vector concept"
-/*! Owns the data space for the elements */
-class Vector
-{
-private:
- double *data;
- const size_t size;
-public:
- Vector(size_t size_arg);
- Vector(const Vector &arg);
- virtual ~Vector();
- inline size_t getSize() const { return size; }
- inline size_t getStride() const { return 1; }
- inline double *getData() { return data; }
- inline const double *getData() const { return data; }
- inline void setAll(double val) { std::fill_n(data, size, val); }
- inline double &operator() (size_t i) { return data[i]; }
- inline const double &operator() (size_t i) const { return data[i]; }
- //! Assignment operator, only works for vectors of same size
- template<class Vec>
- Vector &operator=(const Vec &arg)
- {
- assert(size == arg.getSize());
- const double *p2 = arg.getData();
- for (double *p1 = data; p1 < data + size; p1++)
- {
- *p1 = *p2;
- p2 += arg.getStride();
- }
- return *this;
- }
- //! The copy assignment operator, which is not generated by the template assignment operator
- /*! See C++ standard, §12.8.9, in the footnote */
- Vector &operator=(const Vector &arg);
-};
-
-//! A vector view (i.e. a subvector of another vector, or a row or column of a matrix), implements the "mutable vector concept"
-/*! Does not own the data space for the elements, so depends on another vector or matrix */
-class VectorView
-{
-private:
- double *const data;
- const size_t size, stride;
-public:
- VectorView(double *data_arg, size_t size_arg, size_t stride_arg);
- /* Can't use a template for the 2 constructors below: this would override the
- constructor which uses a pointer, because the argument list is the same */
- VectorView(Vector &arg, size_t offset, size_t size_arg);
- VectorView(VectorView &arg, size_t offset, size_t size_arg);
- virtual ~VectorView(){};
- inline size_t getSize() const { return size; }
- inline size_t getStride() const { return stride; }
- inline double *getData() { return data; }
- inline const double *getData() const { return data; }
- inline void setAll(double val)
- {
- for (double *p = data; p < data + size*stride; p += stride)
- *p = val;
- }
- inline double &operator() (size_t i) { return data[i*stride]; }
- inline const double &operator() (size_t i) const { return data[i*stride]; }
- //! Assignment operator, only works for vectors of same size
- template<class Vec>
- VectorView &
- operator= (const Vec &arg)
- {
- assert(size == arg.getSize());
- double *p1;
- const double *p2;
- for (p1 = data, p2 = arg.getData(); p1 < data + size*stride; p1 += stride, p2 += arg.getStride())
- *p1 = *p2;
- return *this;
- }
- //! The copy assignment operator, which is not generated by the template assignment operator
- /*! See C++ standard, §12.8.9, in the footnote */
- VectorView &operator=(const VectorView &arg);
-};
-
-//! Like a VectorView, but the data cannot be modified (implements the "vector concept")
-class VectorConstView
-{
-private:
- const double *const data;
- const size_t size, stride;
-public:
- VectorConstView(const double *data_arg, size_t size_arg, size_t stride_arg);
- /* Can't use a template for the 3 constructors below: this would override the
- constructor which uses a pointer, because the argument list is the same */
- VectorConstView(const Vector &arg, size_t offset, size_t size_arg);
- VectorConstView(const VectorView &arg, size_t offset, size_t size_arg);
- VectorConstView(const VectorConstView &arg, size_t offset, size_t size_arg);
-
- virtual ~VectorConstView() {};
- inline size_t getSize() const { return size; }
- inline size_t getStride() const { return stride; }
- inline const double *getData() const { return data; }
- inline const double &operator() (size_t i) const { return data[i*stride]; }
-};
-
-std::ostream &operator<<(std::ostream &out, const Vector &V);
-std::ostream &operator<<(std::ostream &out, const VectorView &V);
-std::ostream &operator<<(std::ostream &out, const VectorConstView &V);
-
-namespace vec
-{
- template<class Vec>
- void
- print(std::ostream &out, const Vec &V)
- {
- for (size_t i = 0; i < V.getSize(); i++)
- out << V(i) << " ";
- out << std::endl;
- }
-
- //! Computes v1 = v1 + v2
- template<class Vec1, class Vec2>
- void
- add(Vec1 &v1, const Vec2 &v2)
- {
- assert(v1.getSize() == v2.getSize());
- double *p1 = v1.getData();
- const double *p2 = v2.getData();
- while (p1 < v1.getData() + v1.getSize() * v1.getStride())
- {
- *p1 += *p2;
- p1 += v1.getStride();
- p2 += v2.getStride();
- }
- }
-
- //! Computes v1 = v1 - v2
- template<class Vec1, class Vec2>
- void
- sub(Vec1 &v1, const Vec2 &v2)
- {
- assert(v1.getSize() == v2.getSize());
- double *p1 = v1.getData();
- const double *p2 = v2.getData();
- while (p1 < v1.getData() + v1.getSize() * v1.getStride())
- {
- *p1 -= *p2;
- p1 += v1.getStride();
- p2 += v2.getStride();
- }
- }
-
- //! Does v = -v
- template<class Vec>
- void
- negate(Vec &v)
- {
- double *p = v.getData();
- while (p < v.getData() + v.getSize() * v.getStride())
- {
- *p = -*p;
- p += v.getStride();
- }
- }
-
- // Computes the infinite norm of a vector
- template<class Vec>
- double
- nrminf(const Vec &v)
- {
- double nrm = 0;
- const double *p = v.getData();
- while (p < v.getData() + v.getSize() * v.getStride())
- {
- if (fabs(*p) > nrm)
- nrm = fabs(*p);
- p += v.getStride();
- }
- return nrm;
- }
-
- // Computes the sum, min and max of a vector
- // and returns double mean=sum/size
- template<class Vec>
- double
- meanSumMinMax(double &sum, double &min, double &max, const Vec &v)
- {
- sum = 0;
- min = max = v(0);
- const double *p = v.getData();
- while (p < v.getData() + v.getSize() * v.getStride())
- {
- if ((*p) > max)
- max = (*p);
- if ((*p) < min)
- min = (*p);
- sum += *p;
- p += v.getStride();
- }
- return sum/v.getSize();
- }
-} // End of namespace
-
-#endif
diff --git a/mex/sources/estimation/libmat/tests/Makefile.am b/mex/sources/estimation/libmat/tests/Makefile.am
deleted file mode 100644
index 7223fe01de26281bcaf8c0f19b1454b06c18a31d..0000000000000000000000000000000000000000
--- a/mex/sources/estimation/libmat/tests/Makefile.am
+++ /dev/null
@@ -1,22 +0,0 @@
-check_PROGRAMS = test-qr test-gsd test-lu test-repmat
-
-test_qr_SOURCES = ../Matrix.cc ../Vector.cc ../QRDecomposition.cc test-qr.cc
-test_qr_LDADD = $(LAPACK_LIBS) $(BLAS_LIBS) $(LIBS) $(FLIBS)
-test_qr_CPPFLAGS = -I.. -I../../../
-
-test_gsd_SOURCES = ../Matrix.cc ../Vector.cc ../GeneralizedSchurDecomposition.cc test-gsd.cc
-test_gsd_LDADD = $(LAPACK_LIBS) $(BLAS_LIBS) $(LIBS) $(FLIBS)
-test_gsd_CPPFLAGS = -I.. -I../../../
-
-test_lu_SOURCES = ../Matrix.cc ../Vector.cc ../LUSolver.cc test-lu.cc
-test_lu_LDADD = $(LAPACK_LIBS) $(BLAS_LIBS) $(LIBS) $(FLIBS)
-test_lu_CPPFLAGS = -I.. -I../../../
-
-test_repmat_SOURCES = ../Matrix.cc ../Vector.cc test-repmat.cc
-test_repmat_CPPFLAGS = -I..
-
-check-local:
- ./test-qr
- ./test-gsd
- ./test-lu
- ./test-repmat
diff --git a/mex/sources/estimation/libmat/tests/test-gsd.cc b/mex/sources/estimation/libmat/tests/test-gsd.cc
deleted file mode 100644
index fd8dea7f651e6d6e6d96344d9054337ead5a7055..0000000000000000000000000000000000000000
--- a/mex/sources/estimation/libmat/tests/test-gsd.cc
+++ /dev/null
@@ -1,61 +0,0 @@
-/*
- * Copyright (C) 2010 Dynare Team
- *
- * This file is part of Dynare.
- *
- * Dynare is free software: you can redistribute it and/or modify
- * it under the terms of the GNU General Public License as published by
- * the Free Software Foundation, either version 3 of the License, or
- * (at your option) any later version.
- *
- * Dynare is distributed in the hope that it will be useful,
- * but WITHOUT ANY WARRANTY; without even the implied warranty of
- * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
- * GNU General Public License for more details.
- *
- * You should have received a copy of the GNU General Public License
- * along with Dynare. If not, see <http://www.gnu.org/licenses/>.
- */
-
-#include <iostream>
-
-#include "GeneralizedSchurDecomposition.hh"
-
-int
-main(int argc, char **argv)
-{
- size_t n = 3;
- double D_data[] = { 1, 2, 3,
- 4, 5, 6,
- 7, 8, 9 };
- double E_data[] = { 1, -3, 4,
- -7, 9, 1,
- -3, 4, 0 };
- MatrixView D(D_data, n, n, n), E(E_data, n, n, n);
-
- // Need to transpose because internally matrices are in column-major order
- mat::transpose(D);
- mat::transpose(E);
-
- std::cout << "D =" << std::endl << D << std::endl;
- std::cout << "E =" << std::endl << E << std::endl;
-
- GeneralizedSchurDecomposition GSD(n, 1.00001);
-
- Matrix S(n), T(n), Z(n);
- size_t sdim;
-
- GSD.compute(D, E, S, T, Z, sdim);
-
- std::cout << "S =" << std::endl << S << std::endl;
- std::cout << "T =" << std::endl << T << std::endl;
- std::cout << "Z =" << std::endl << Z << std::endl;
-
- Vector eig_real(n), eig_cmplx(n);
- GSD.getGeneralizedEigenvalues(eig_real, eig_cmplx);
-
- std::cout << "Real part of generalized eigenvalues: " << std::endl << eig_real << std::endl;
- std::cout << "Complex part of generalized eigenvalues: " << std::endl << eig_cmplx << std::endl;
-
- return 0;
-}
diff --git a/mex/sources/estimation/libmat/tests/test-lu.cc b/mex/sources/estimation/libmat/tests/test-lu.cc
deleted file mode 100644
index b41af33b3c16df76a3ce5e06f4cafed6a9c63fc6..0000000000000000000000000000000000000000
--- a/mex/sources/estimation/libmat/tests/test-lu.cc
+++ /dev/null
@@ -1,60 +0,0 @@
-/*
- * Copyright (C) 2010 Dynare Team
- *
- * This file is part of Dynare.
- *
- * Dynare is free software: you can redistribute it and/or modify
- * it under the terms of the GNU General Public License as published by
- * the Free Software Foundation, either version 3 of the License, or
- * (at your option) any later version.
- *
- * Dynare is distributed in the hope that it will be useful,
- * but WITHOUT ANY WARRANTY; without even the implied warranty of
- * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
- * GNU General Public License for more details.
- *
- * You should have received a copy of the GNU General Public License
- * along with Dynare. If not, see <http://www.gnu.org/licenses/>.
- */
-
-#include <iostream>
-
-#include "BlasBindings.hh"
-#include "LUSolver.hh"
-
-int
-main(int argc, char **argv)
-{
- size_t m = 4, n = 3;
-
- double A_data[] = { -1, 2, 3,
- 4, -5, 6,
- 7, 8, -9 };
- double B_data[] = { 1, -3, 4, 5,
- -7, 9, 1, 7,
- -3, 4, 0, -2 };
- MatrixView A(A_data, n, n, n), B_prime(B_data, m, n, m);
- Matrix B(n, m);
-
- mat::transpose(A);
- mat::transpose(B, B_prime);
-
- std::cout << "A =" << std::endl << A << std::endl
- << "B =" << std::endl << B << std::endl;
-
- LUSolver LU(n);
-
- LU.invMult("N", A, B);
-
- std::cout << "A\\B =" << std::endl << B;
-
- // Check this is the right result
- double C_data[] = { -1.0500, 1.3750, 0.0833, 0.6250,
- 0.3000, -0.7500, 0.8333, 0.7500,
- -0.2167, -0.0417, 0.8056, 1.3750 };
- MatrixView C_prime(C_data, m, n, m);
- Matrix C(n, m);
- mat::transpose(C, C_prime);
- mat::sub(B, C);
- assert(mat::nrminf(B) < 1e-4);
-}
diff --git a/mex/sources/estimation/libmat/tests/test-qr.cc b/mex/sources/estimation/libmat/tests/test-qr.cc
deleted file mode 100644
index f73d85488222d9aa53ff7c8e1af2574d49864f60..0000000000000000000000000000000000000000
--- a/mex/sources/estimation/libmat/tests/test-qr.cc
+++ /dev/null
@@ -1,66 +0,0 @@
-/*
- * Copyright (C) 2010 Dynare Team
- *
- * This file is part of Dynare.
- *
- * Dynare is free software: you can redistribute it and/or modify
- * it under the terms of the GNU General Public License as published by
- * the Free Software Foundation, either version 3 of the License, or
- * (at your option) any later version.
- *
- * Dynare is distributed in the hope that it will be useful,
- * but WITHOUT ANY WARRANTY; without even the implied warranty of
- * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
- * GNU General Public License for more details.
- *
- * You should have received a copy of the GNU General Public License
- * along with Dynare. If not, see <http://www.gnu.org/licenses/>.
- */
-
-#include <iostream>
-
-#include "BlasBindings.hh"
-#include "QRDecomposition.hh"
-
-int
-main(int argc, char **argv)
-{
- size_t m = 4, n = 3;
- Matrix S(m, n), Q(m), A(m, n), B(m), S2(m, n);
- QRDecomposition QRD(m, n, m);
-
- for (size_t i = 0; i < m; i++)
- for (size_t j = 0; j < n; j++)
- S(i, j) = i*n + j + 1;
-
- std::cout << "Matrix to be decomposed:" << std::endl << S << std::endl;
-
- mat::set_identity(Q);
-
- S2 = S;
- QRD.computeAndLeftMultByQ(S2, "N", Q);
-
- std::cout << "Q =" << std::endl << Q << std::endl;
-
- blas::gemm("T", "N", 1.0, Q, Q, 0.0, B);
-
- std::cout << "Q'*Q =" << std::endl << B << std::endl;
-
- for (size_t j = 0; j < n; j++)
- mat::col_set(S2, j, j+1, m-j-1, 0);
-
- std::cout << "R =" << std::endl << S2 << std::endl;
-
- blas::gemm("N", "N", 1.0, Q, S2, 0.0, A);
-
- std::cout << "Q*R =" << std::endl << A << std::endl;
-
- // Check values
- Matrix B2(m);
- mat::set_identity(B2);
- mat::sub(B2, B);
- assert(mat::nrminf(B2) < 1e-4);
-
- mat::sub(A, S);
- assert(mat::nrminf(A) < 1e-4);
-}
diff --git a/mex/sources/estimation/libmat/tests/test-repmat.cc b/mex/sources/estimation/libmat/tests/test-repmat.cc
deleted file mode 100644
index f8581eea30cafaa1d944280acf07d833bc6abd2d..0000000000000000000000000000000000000000
--- a/mex/sources/estimation/libmat/tests/test-repmat.cc
+++ /dev/null
@@ -1,70 +0,0 @@
-/*
- * Copyright (C) 2010 Dynare Team
- *
- * This file is part of Dynare.
- *
- * Dynare is free software: you can redistribute it and/or modify
- * it under the terms of the GNU General Public License as published by
- * the Free Software Foundation, either version 3 of the License, or
- * (at your option) any later version.
- *
- * Dynare is distributed in the hope that it will be useful,
- * but WITHOUT ANY WARRANTY; without even the implied warranty of
- * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
- * GNU General Public License for more details.
- *
- * You should have received a copy of the GNU General Public License
- * along with Dynare. If not, see <http://www.gnu.org/licenses/>.
- */
-
-#include <iostream>
-#include "Matrix.hh"
-
-int
-main(int argc, char **argv)
-{
- size_t m = 4, n = 3;
- Matrix S(m, n), A(5*m, 3*n), A2(5*m, 3*n);
-
- for (size_t i = 0; i < m; i++)
- for (size_t j = 0; j < n; j++)
- S(i, j) = i*n + j + 1;
-
- std::cout << "Matrix to be tiled:" << std::endl << S << std::endl;
-
- Matrix S1(m, 2 *n), S2(2*m, n);
- std::vector<size_t> toC(n), toR(m);
- for (size_t i = 0; i < n; i++)
- toC[i] = 2*i;
-
- for (size_t j = 0; j < m; j++)
- toR[j] = m-j-1;
-
- mat::assignByVectors(S1, mat::nullVec, toC, S, mat::nullVec, mat::nullVec);
- std::cout << "Matrix assigned and col reorder by vectors:" << std::endl << S1 << std::endl;
-
- mat::assignByVectors(S2, toR, mat::nullVec, S, mat::nullVec, mat::nullVec);
- std::cout << "Matrix assigned and row ereorder by vectors:" << std::endl << S2 << std::endl;
-
- mat::assignByVectors(S1, toR, toC, S, mat::nullVec, mat::nullVec);
- std::cout << "Matrix assigned by vectors:" << std::endl << S1 << std::endl;
-
- mat::repmat(S, 5, 3, A);
- std::cout << "Tiled=" << std::endl << A << std::endl;
-
- A2 = A;
- bool b = mat::isDiff(A, A2, 0.0000001);
- std::cout << "No Diff=" << b << std::endl;
- mat::add(A, 0.000001);
- b = mat::isDiff(A, A2, 0.0000001);
- std::cout << "Yes Diff=" << b << std::endl;
- Matrix A4(5), A5(5);
- A4.setAll(1.0);
- A5.setAll(1.0);
- b = mat::isDiffSym(A4, A5, 0.0000001);
- std::cout << "No DiffSym=" << b << std::endl;
- mat::sub(A4, 0.0001);
- b = mat::isDiffSym(A4, A5, 0.0000001);
- std::cout << "Yes DiffSym=" << b << std::endl;
-
-}
diff --git a/mex/sources/estimation/logMHMCMCposterior.cc b/mex/sources/estimation/logMHMCMCposterior.cc
deleted file mode 100644
index c388767af8d8114f7dca05089337eb5c8d71cfcc..0000000000000000000000000000000000000000
--- a/mex/sources/estimation/logMHMCMCposterior.cc
+++ /dev/null
@@ -1,790 +0,0 @@
-/*
- * Copyright (C) 2010-2012 Dynare Team
- *
- * This file is part of Dynare.
- *
- * Dynare is free software: you can redistribute it and/or modify
- * it under the terms of the GNU General Public License as published by
- * the Free Software Foundation, either version 3 of the License, or
- * (at your option) any later version.
- *
- * Dynare is distributed in the hope that it will be useful,
- * but WITHOUT ANY WARRANTY; without even the implied warranty of
- * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
- * GNU General Public License for more details.
- *
- * You should have received a copy of the GNU General Public License
- * along with Dynare. If not, see <http://www.gnu.org/licenses/>.
- */
-
-#include <string>
-#include <vector>
-#include <algorithm>
-#include <functional>
-
-#include "Vector.hh"
-#include "Matrix.hh"
-#include "LogPosteriorDensity.hh"
-#include "RandomWalkMetropolisHastings.hh"
-
-#include <dynmex.h>
-#if defined MATLAB_MEX_FILE
-# include "mat.h"
-#else // OCTAVE_MEX_FILE e.t.c.
-# include "matio.h"
-#endif
-
-#if defined(_WIN32) || defined(__CYGWIN32__) || defined(WINDOWS)
-# define DIRECTORY_SEPARATOR "\\"
-#else
-# define DIRECTORY_SEPARATOR "/"
-#endif
-
-class LogMHMCMCposteriorMexErrMsgTxtException
-{
-public:
- std::string errMsg;
- LogMHMCMCposteriorMexErrMsgTxtException(const std::string &msg) : errMsg(msg)
- {
- }
- inline const char *getErrMsg() { return errMsg.c_str(); }
-};
-
-void
-fillEstParamsInfo(const mxArray *estim_params_info, EstimatedParameter::pType type,
- std::vector<EstimatedParameter> &estParamsInfo)
-{
- // execute once only
- static const mxArray *bayestopt_ = mexGetVariablePtr("global", "bayestopt_");
- static const mxArray *bayestopt_ubp = mxGetField(bayestopt_, 0, "ub"); // upper bound
- static const mxArray *bayestopt_lbp = mxGetField(bayestopt_, 0, "lb"); // lower bound
- static const mxArray *bayestopt_p1p = mxGetField(bayestopt_, 0, "p1"); // prior mean
- static const mxArray *bayestopt_p2p = mxGetField(bayestopt_, 0, "p2"); // prior standard deviation
- static const mxArray *bayestopt_p3p = mxGetField(bayestopt_, 0, "p3"); // lower bound
- static const mxArray *bayestopt_p4p = mxGetField(bayestopt_, 0, "p4"); // upper bound
- static const mxArray *bayestopt_p6p = mxGetField(bayestopt_, 0, "p6"); // first hyper-parameter (\alpha for the BETA and GAMMA distributions, s for the INVERSE GAMMAs, expectation for the GAUSSIAN distribution, lower bound for the UNIFORM distribution).
- static const mxArray *bayestopt_p7p = mxGetField(bayestopt_, 0, "p7"); // second hyper-parameter (\beta for the BETA and GAMMA distributions, \nu for the INVERSE GAMMAs, standard deviation for the GAUSSIAN distribution, upper bound for the UNIFORM distribution).
- static const mxArray *bayestopt_jscalep = mxGetField(bayestopt_, 0, "jscale"); // MCMC jump scale
-
- static const size_t bayestopt_size = mxGetM(bayestopt_);
- static const VectorConstView bayestopt_ub(mxGetPr(bayestopt_ubp), bayestopt_size, 1);
- static const VectorConstView bayestopt_lb(mxGetPr(bayestopt_lbp), bayestopt_size, 1);
- static const VectorConstView bayestopt_p1(mxGetPr(bayestopt_p1p), bayestopt_size, 1); //=mxGetField(bayestopt_, 0, "p1");
- static const VectorConstView bayestopt_p2(mxGetPr(bayestopt_p2p), bayestopt_size, 1); //=mxGetField(bayestopt_, 0, "p2");
- static const VectorConstView bayestopt_p3(mxGetPr(bayestopt_p3p), bayestopt_size, 1); //=mxGetField(bayestopt_, 0, "p3");
- static const VectorConstView bayestopt_p4(mxGetPr(bayestopt_p4p), bayestopt_size, 1); //=mxGetField(bayestopt_, 0, "p4");
- static const VectorConstView bayestopt_p6(mxGetPr(bayestopt_p6p), bayestopt_size, 1); //=mxGetField(bayestopt_, 0, "p6");
- static const VectorConstView bayestopt_p7(mxGetPr(bayestopt_p7p), bayestopt_size, 1); //=mxGetField(bayestopt_, 0, "p7");
- static const VectorConstView bayestopt_jscale(mxGetPr(bayestopt_jscalep), bayestopt_size, 1); //=mxGetField(bayestopt_, 0, "jscale");
-
- // loop processsing
- size_t m = mxGetM(estim_params_info), n = mxGetN(estim_params_info);
- MatrixConstView epi(mxGetPr(estim_params_info), m, n, m);
- size_t bayestopt_count = estParamsInfo.size();
-
- for (size_t i = 0; i < m; i++)
- {
- size_t col = 0;
- size_t id1 = (size_t) epi(i, col++) - 1;
- size_t id2 = 0;
- if (type == EstimatedParameter::shock_Corr
- || type == EstimatedParameter::measureErr_Corr)
- id2 = (size_t) epi(i, col++) - 1;
- col++; // Skip init_val #2 or #3
- double par_low_bound = bayestopt_lb(bayestopt_count); col++; //#3 epi(i, col++);
- double par_up_bound = bayestopt_ub(bayestopt_count); col++; //#4 epi(i, col++);
- Prior::pShape shape = (Prior::pShape) epi(i, col++);
- double mean = epi(i, col++);
- double std = epi(i, col++);
- double low_bound = bayestopt_p3(bayestopt_count);
- double up_bound = bayestopt_p4(bayestopt_count);
- double fhp = bayestopt_p6(bayestopt_count); // double p3 = epi(i, col++);
- double shp = bayestopt_p7(bayestopt_count); // double p4 = epi(i, col++);
-
- Prior *p = Prior::constructPrior(shape, mean, std, low_bound, up_bound, fhp, shp); //1.0,INFINITY);//p3, p4);
-
- // Only one subsample
- std::vector<size_t> subSampleIDs;
- subSampleIDs.push_back(0);
- estParamsInfo.push_back(EstimatedParameter(type, id1, id2, subSampleIDs,
- par_low_bound, par_up_bound, p));
- bayestopt_count++;
- }
-}
-
-int
-sampleMHMC(LogPosteriorDensity &lpd, RandomWalkMetropolisHastings &rwmh,
- VectorView &steadyState, VectorConstView &estParams, VectorView &deepParams, const MatrixConstView &data,
- MatrixView &Q, Matrix &H, size_t presampleStart, int &info, const VectorConstView &nruns,
- size_t fblock, size_t nBlocks, Proposal pdd, EstimatedParametersDescription &epd,
- const std::string &resultsFileStem, size_t console_mode, size_t load_mh_file)
-{
- enum {iMin, iMax};
- int iret = 0; // return value
- std::vector<size_t> OpenOldFile(nBlocks, 0);
- size_t jloop = 0, irun, j; // counters
- double dsum, dmax, dmin, sux = 0, jsux = 0;
- std::string mhFName;
- std::stringstream ssFName;
-#if defined MATLAB_MEX_FILE
- MATFile *drawmat; // MCMC draws output file pointer
- int matfStatus;
-#else // OCTAVE_MEX_FILE e.t.c.
- int dims[2];
- mat_t *drawmat;
- matvar_t *matvar;
- int matfStatus;
-#endif
- FILE *fidlog; // log file
- size_t npar = estParams.getSize();
- Matrix MinMax(npar, 2);
-
- const mxArray *InitSizeArrayPtr = mexGetVariablePtr("caller", "InitSizeArray");
- if (InitSizeArrayPtr == NULL)
- {
- mexPrintf("Metropolis-Hastings myinputs field InitSizeArrayPtr Initialisation failed!\n");
- return (-1);
- }
- const VectorConstView InitSizeArrayVw(mxGetPr(InitSizeArrayPtr), nBlocks, 1);
- Vector InitSizeArray(InitSizeArrayVw.getSize());
- InitSizeArray = InitSizeArrayVw;
- //const mxArray *flinePtr = mxGetField(myinputs, 0, "fline");
- const mxArray *flinePtr = mexGetVariable("caller", "fline");
- if (flinePtr == NULL)
- {
- mexPrintf("Metropolis-Hastings myinputs field fline Initialisation failed!\n");
- return (-1);
- }
- VectorView fline(mxGetPr(flinePtr), nBlocks, 1);
-
- mxArray *NewFileArrayPtr = mexGetVariable("caller", "NewFile");
- if (NewFileArrayPtr == NULL)
- {
- mexPrintf("Metropolis-Hastings myinputs fields NewFileArrayPtr Initialisation failed!\n");
- return (-1);
- }
- VectorView NewFileVw(mxGetPr(NewFileArrayPtr), nBlocks, 1);
- //Vector NewFile(NewFileVw.getSize());
- //NewFile = NewFileVw;
-
- const mxArray *MAX_nrunsPtr = mexGetVariablePtr("caller", "MAX_nruns");
- const size_t MAX_nruns = (size_t) mxGetScalar(MAX_nrunsPtr);
-
- const mxArray *blockStartParamsPtr = mexGetVariable("caller", "ix2");
- MatrixView blockStartParamsMxVw(mxGetPr(blockStartParamsPtr), nBlocks, npar, nBlocks);
- Vector startParams(npar);
-
- const mxArray *mxFirstLogLikPtr = mexGetVariable("caller", "ilogpo2");
- VectorView FirstLogLiK(mxGetPr(mxFirstLogLikPtr), nBlocks, 1);
-
- const mxArray *record = mexGetVariable("caller", "record");
- //const mxArray *record = mxGetField(myinputs, 0, "record");
- if (record == NULL)
- {
- mexPrintf("Metropolis-Hastings record Initialisation failed!\n");
- return (-1);
- }
- mxArray *AcceptationRatesPtr = mxGetField(record, 0, "AcceptationRates");
- if (AcceptationRatesPtr == NULL)
- {
- mexPrintf("Metropolis-Hastings record AcceptationRatesPtr Initialisation failed!\n");
- return (-1);
- }
- VectorView AcceptationRates(mxGetPr(AcceptationRatesPtr), nBlocks, 1);
-
- mxArray *mxLastParametersPtr = mxGetField(record, 0, "LastParameters");
- MatrixView LastParameters(mxGetPr(mxLastParametersPtr), nBlocks, npar, nBlocks);
- LastParameters = blockStartParamsMxVw;
-
- mxArray *mxLastLogLikPtr = mxGetField(record, 0, "LastLogLiK");
- VectorView LastLogLiK(mxGetPr(mxLastLogLikPtr), nBlocks, 1);
-
- mxArray *mxMhLogPostDensPtr = 0;
- mxArray *mxMhParamDrawsPtr = 0;
- size_t currInitSizeArray = 0;
-
-#if defined MATLAB_MEX_FILE
- // Waitbar
- mxArray *waitBarRhs[3], *waitBarLhs[1];
- waitBarRhs[0] = mxCreateDoubleMatrix(1, 1, mxREAL);
- std::string barTitle;
- std::stringstream ssbarTitle;
- if (console_mode == 0)
- {
- ssbarTitle.clear();
- ssbarTitle.str("");
- ssbarTitle << "Please wait... Metropolis-Hastings " << fblock << "/" << nBlocks << " ...";
- barTitle = ssbarTitle.str();
- waitBarRhs[1] = mxCreateString(barTitle.c_str());
- *mxGetPr(waitBarRhs[0]) = (double) 0.0;
- mexCallMATLAB(1, waitBarLhs, 2, waitBarRhs, "waitbar");
- if (waitBarRhs[1])
- mxDestroyArray(waitBarRhs[1]);
- waitBarRhs[1] = waitBarLhs[0];
- }
-#endif
-
- for (size_t b = fblock; b <= nBlocks; ++b)
- {
- jloop = jloop+1;
-
-#if defined MATLAB_MEX_FILE
- if ((load_mh_file != 0) && (fline(b) > 1) && OpenOldFile[b])
- {
- // load(['./' MhDirectoryName '/' ModelName '_mh' int2str(NewFile(b)) '_blck' int2str(b) '.mat'])
- ssFName.clear();
- ssFName.str("");
- ssFName << resultsFileStem << DIRECTORY_SEPARATOR << "metropolis" << DIRECTORY_SEPARATOR << resultsFileStem << "_mh" << (size_t) NewFileVw(b-1) << "_blck" << b << ".mat";
- mhFName = ssFName.str();
- drawmat = matOpen(mhFName.c_str(), "r");
- mexPrintf("MHMCMC: Using interim partial draws file %s \n", mhFName.c_str());
- if (drawmat == 0)
- {
- fline(b) = 1;
- mexPrintf("Error in MH: Can not open old draws Mat file for reading: %s \n \
- Starting a new file instead! \n", mhFName.c_str());
- }
- else
- {
- currInitSizeArray = (size_t) InitSizeArray(b-1);
- mxMhParamDrawsPtr = matGetVariable(drawmat, "x2");
- mxMhLogPostDensPtr = matGetVariable(drawmat, "logpo2");
- matClose(drawmat);
- OpenOldFile[b] = 1;
- }
- } // end if
- if (console_mode == 0)
- {
- ssbarTitle.clear();
- ssbarTitle.str("");
- ssbarTitle << "Please wait... Metropolis-Hastings " << b << "/" << nBlocks << " ...";
- barTitle = ssbarTitle.str();
- waitBarRhs[2] = mxCreateString(barTitle.c_str());
- //strcpy( *mxGetPr(waitBarRhs[1]), mhFName.c_str());
- *mxGetPr(waitBarRhs[0]) = (double) 0.0;
- mexCallMATLAB(0, NULL, 3, waitBarRhs, "waitbar");
- mxDestroyArray(waitBarRhs[2]);
- }
-#else //if defined OCTAVE_MEX_FILE
- if ((load_mh_file != 0) && (fline(b) > 1) && OpenOldFile[b])
- {
- // load(['./' MhDirectoryName '/' ModelName '_mh' int2str(NewFile(b)) '_blck' int2str(b) '.mat'])
- if ((currInitSizeArray != (size_t) InitSizeArray(b-1)) && OpenOldFile[b] != 1)
- {
- // new or different size result arrays/matrices
- currInitSizeArray = (size_t) InitSizeArray(b-1);
- if (mxMhLogPostDensPtr)
- mxDestroyArray(mxMhLogPostDensPtr); // log post density array
- mxMhLogPostDensPtr = mxCreateDoubleMatrix(currInitSizeArray, 1, mxREAL);
- if (mxMhLogPostDensPtr == NULL)
- {
- mexPrintf("Metropolis-Hastings mxMhLogPostDensPtr Initialisation failed!\n");
- return (-1);
- }
- if (mxMhParamDrawsPtr)
- mxDestroyArray(mxMhParamDrawsPtr); // accepted MCMC MH draws
- mxMhParamDrawsPtr = mxCreateDoubleMatrix(currInitSizeArray, npar, mxREAL);
- if (mxMhParamDrawsPtr == NULL)
- {
- mexPrintf("Metropolis-Hastings mxMhParamDrawsPtr Initialisation failed!\n");
- return (-1);
- }
- }
-
- ssFName.clear();
- ssFName.str("");
- ssFName << resultsFileStem << DIRECTORY_SEPARATOR << "metropolis" << DIRECTORY_SEPARATOR << resultsFileStem << "_mh" << (size_t) NewFileVw(b-1) << "_blck" << b << ".mat";
- mhFName = ssFName.str();
- drawmat = Mat_Open(mhFName.c_str(), MAT_ACC_RDONLY);
- if (drawmat == NULL)
- {
- fline(b) = 1;
- mexPrintf("Error in MH: Can not open old draws Mat file for reading: %s \n \
- Starting a new file instead! \n", mhFName.c_str());
- }
- else
- {
- int start[2] = {0, 0}, edge[2] = {2, 2}, stride[2] = {1, 1}, err = 0;
- mexPrintf("MHMCMC: Using interim partial draws file %s \n", mhFName.c_str());
- // matvar = Mat_VarReadInfo(drawmat, "x2");
- matvar = Mat_VarReadInfo(drawmat, (char *) "x2");
- if (matvar == NULL)
- {
- fline(b) = 1;
- mexPrintf("Error in MH: Can not read old draws Mat file for reading: %s \n \
- Starting a new file instead! \n", mhFName.c_str());
- }
- else
- {
- // GetVariable(drawmat, "x2");
- dims[0] = matvar->dims[0]-1;
- dims[1] = matvar->dims[1]-1;
- err = Mat_VarReadData(drawmat, matvar, mxGetPr(mxMhParamDrawsPtr), start, stride, matvar->dims);
- if (err)
- {
- fline(b) = 1;
- mexPrintf("Error in MH: Can not retreive old draws from Mat file: %s \n \
- Starting a new file instead! \n", mhFName.c_str());
- }
- Mat_VarFree(matvar);
- }
- //mxMhLogPostDensPtr = Mat_GetVariable(drawmat, "logpo2");
- matvar = Mat_VarReadInfo(drawmat, (char *) "logpo2");
- if (matvar == NULL)
- {
- fline(b) = 1;
- mexPrintf("Error in MH: Can not read old logPos Mat file for reading: %s \n \
- Starting a new file instead! \n", mhFName.c_str());
- }
- else
- {
- // GetVariable(drawmat, "x2");
- dims[0] = matvar->dims[0]-1;
- dims[1] = matvar->dims[1]-1;
- err = Mat_VarReadData(drawmat, matvar, mxGetPr(mxMhLogPostDensPtr), start, stride, matvar->dims);
- if (err)
- {
- fline(b) = 1;
- mexPrintf("Error in MH: Can not retreive old logPos from Mat file: %s \n \
- Starting a new file instead! \n", mhFName.c_str());
- }
- Mat_VarFree(matvar);
- }
- Mat_Close(drawmat);
- OpenOldFile[b] = 1;
- }
- } // end if
-
-#endif
-
- VectorView LastParametersRow = mat::get_row(LastParameters, b-1);
-
- sux = 0.0;
- jsux = 0;
- irun = (size_t) fline(b-1);
- j = 0; //1;
- while (j < nruns(b-1))
- {
- if ((currInitSizeArray != (size_t) InitSizeArray(b-1)) && OpenOldFile[b] != 1)
- {
- // new or different size result arrays/matrices
- currInitSizeArray = (size_t) InitSizeArray(b-1);
- if (mxMhLogPostDensPtr)
- mxDestroyArray(mxMhLogPostDensPtr); // log post density array
- mxMhLogPostDensPtr = mxCreateDoubleMatrix(currInitSizeArray, 1, mxREAL);
- if (mxMhLogPostDensPtr == NULL)
- {
- mexPrintf("Metropolis-Hastings mxMhLogPostDensPtr Initialisation failed!\n");
- return (-1);
- }
- if (mxMhParamDrawsPtr)
- mxDestroyArray(mxMhParamDrawsPtr); // accepted MCMC MH draws
- mxMhParamDrawsPtr = mxCreateDoubleMatrix(currInitSizeArray, npar, mxREAL);
- if (mxMhParamDrawsPtr == NULL)
- {
- mexPrintf("Metropolis-Hastings mxMhParamDrawsPtr Initialisation failed!\n");
- return (-1);
- }
- }
- startParams = LastParametersRow;
- VectorView mhLogPostDens(mxGetPr(mxMhLogPostDensPtr), currInitSizeArray, (size_t) 1);
- MatrixView mhParamDraws(mxGetPr(mxMhParamDrawsPtr), currInitSizeArray, npar, currInitSizeArray);
- try
- {
- jsux = rwmh.compute(mhLogPostDens, mhParamDraws, steadyState, startParams, deepParams, data, Q, H,
- presampleStart, info, irun, currInitSizeArray, lpd, pdd, epd);
- irun = currInitSizeArray;
- sux += jsux*currInitSizeArray;
- j += currInitSizeArray; //j=j+1;
- }
- catch (const TSException &tse)
- {
- iret = -100;
- mexPrintf(" TSException Exception in RandomWalkMH dynamic_dll: %s \n", (tse.getMessage()).c_str());
- goto cleanup;
- }
- catch (const DecisionRules::BlanchardKahnException &bke)
- {
- iret = -90;
- mexPrintf(" Too many Blanchard-Kahn Exceptions in RandomWalkMH : n_fwrd_vars %d n_explosive_eigenvals %d \n", bke.n_fwrd_vars, bke.n_explosive_eigenvals);
- goto cleanup;
- }
- catch (const GeneralizedSchurDecomposition::GSDException &gsde)
- {
- iret = -80;
- mexPrintf(" GeneralizedSchurDecomposition Exception in RandomWalkMH: info %d, n %d \n", gsde.info, gsde.n);
- goto cleanup;
- }
- catch (const LUSolver::LUException &lue)
- {
- iret = -70;
- mexPrintf(" LU Exception in RandomWalkMH : info %d \n", lue.info);
- goto cleanup;
- }
- catch (const VDVEigDecomposition::VDVEigException &vdve)
- {
- iret = -60;
- mexPrintf(" VDV Eig Exception in RandomWalkMH : %s , info: %d\n", vdve.message.c_str(), vdve.info);
- goto cleanup;
- }
- catch (const DiscLyapFast::DLPException &dlpe)
- {
- iret = -50;
- mexPrintf(" Lyapunov solver Exception in RandomWalkMH : %s , info: %d\n", dlpe.message.c_str(), dlpe.info);
- goto cleanup;
- }
- catch (const std::runtime_error &re)
- {
- iret = -3;
- mexPrintf(" Runtime Error Exception in RandomWalkMH: %s \n", re.what());
- goto cleanup;
- }
- catch (const std::exception &e)
- {
- iret = -2;
- mexPrintf(" Standard System Exception in RandomWalkMH: %s \n", e.what());
- goto cleanup;
- }
- catch (...)
- {
- iret = -1000;
- mexPrintf(" Unknown unhandled Exception in RandomWalkMH! %s \n");
- goto cleanup;
- }
-
-#if defined MATLAB_MEX_FILE
- if (console_mode)
- mexPrintf(" MH: Computing Metropolis-Hastings (chain %d/%d): %3.f \b%% done, acceptance rate: %3.f \b%%\r", b, nBlocks, 100 * j/nruns(b-1), 100 * sux / j);
- else
- {
- // Waitbar
- ssbarTitle.clear();
- ssbarTitle.str("");
- ssbarTitle << "Metropolis-Hastings : " << b << "/" << nBlocks << " Acceptance: " << 100 * sux/j << "%";
- barTitle = ssbarTitle.str();
- waitBarRhs[2] = mxCreateString(barTitle.c_str());
- *mxGetPr(waitBarRhs[0]) = j / nruns(b-1);
- mexCallMATLAB(0, NULL, 3, waitBarRhs, "waitbar");
- mxDestroyArray(waitBarRhs[2]);
-
- }
-
- // % Now I save the simulations
- // save draw 2 mat file ([MhDirectoryName '/' ModelName '_mh' int2str(NewFile(b)) '_blck' int2str(b) '.mat'],'x2','logpo2');
- ssFName.clear();
- ssFName.str("");
- ssFName << resultsFileStem << DIRECTORY_SEPARATOR << "metropolis" << DIRECTORY_SEPARATOR << resultsFileStem << "_mh" << (size_t) NewFileVw(b-1) << "_blck" << b << ".mat";
- mhFName = ssFName.str();
- drawmat = matOpen(mhFName.c_str(), "w");
- if (drawmat == 0)
- {
- mexPrintf("Error in MH: Can not open draws Mat file for writing: %s \n", mhFName.c_str());
- exit(1);
- }
- matfStatus = matPutVariable(drawmat, "x2", mxMhParamDrawsPtr);
- if (matfStatus)
- {
- mexPrintf("Error in MH: Can not use draws Mat file for writing: %s \n", mhFName.c_str());
- exit(1);
- }
- matfStatus = matPutVariable(drawmat, "logpo2", mxMhLogPostDensPtr);
- if (matfStatus)
- {
- mexPrintf("Error in MH: Can not usee draws Mat file for writing: %s \n", mhFName.c_str());
- exit(1);
- }
- matClose(drawmat);
-#else
-
- printf(" MH: Computing Metropolis-Hastings (chain %d/%d): %3.f \b%% done, acceptance rate: %3.f \b%%\r", b, nBlocks, 100 * j/nruns(b-1), 100 * sux / j);
- // % Now I save the simulations
- // save draw 2 mat file ([MhDirectoryName '/' ModelName '_mh' int2str(NewFile(b)) '_blck' int2str(b) '.mat'],'x2','logpo2');
- ssFName.clear();
- ssFName.str("");
- ssFName << resultsFileStem << DIRECTORY_SEPARATOR << "metropolis" << DIRECTORY_SEPARATOR << resultsFileStem << "_mh" << (size_t) NewFileVw(b-1) << "_blck" << b << ".mat";
- mhFName = ssFName.str();
-
- drawmat = Mat_Open(mhFName.c_str(), MAT_ACC_RDWR);
- if (drawmat == 0)
- {
- mexPrintf("Error in MH: Can not open draws Mat file for writing: %s \n", mhFName.c_str());
- exit(1);
- }
- dims[0] = currInitSizeArray;
- dims[1] = npar;
- matvar = Mat_VarCreate("x2", MAT_C_DOUBLE, MAT_T_DOUBLE, 2, dims, mxGetPr(mxMhParamDrawsPtr), 0);
- matfStatus = Mat_VarWrite(drawmat, matvar, 0);
- Mat_VarFree(matvar);
- if (matfStatus)
- {
- mexPrintf("Error in MH: Can not use draws Mat file for writing: %s \n", mhFName.c_str());
- exit(1);
- }
- //matfStatus = matPutVariable(drawmat, "logpo2", mxMhLogPostDensPtr);
- dims[1] = 1;
- matvar = Mat_VarCreate("logpo2", MAT_C_DOUBLE, MAT_T_DOUBLE, 2, dims, mxGetPr(mxMhLogPostDensPtr), 0);
- matfStatus = Mat_VarWrite(drawmat, matvar, 0);
- Mat_VarFree(matvar);
- if (matfStatus)
- {
- mexPrintf("Error in MH: Can not usee draws Mat file for writing: %s \n", mhFName.c_str());
- exit(1);
- }
- Mat_Close(drawmat);
-#endif
-
- // save log to fidlog = fopen([MhDirectoryName '/metropolis.log'],'a');
- ssFName.str("");
- ssFName << resultsFileStem << DIRECTORY_SEPARATOR << "metropolis" << DIRECTORY_SEPARATOR << "metropolis.log";
- mhFName = ssFName.str();
- fidlog = fopen(mhFName.c_str(), "a");
- fprintf(fidlog, "\n");
- fprintf(fidlog, "%% Mh%dBlck%lu ( %s %s )\n", (int) NewFileVw(b-1), b, __DATE__, __TIME__);
- fprintf(fidlog, " \n");
- fprintf(fidlog, " Number of simulations.: %lu \n", currInitSizeArray); // (length(logpo2)) ');
- fprintf(fidlog, " Acceptation rate......: %f \n", jsux);
- fprintf(fidlog, " Posterior mean........:\n");
- for (size_t i = 0; i < npar; ++i)
- {
- VectorView mhpdColVw = mat::get_col(mhParamDraws, i);
- fprintf(fidlog, " params: %lu : %f \n", i+1, vec::meanSumMinMax(dsum, dmin, dmax, mhpdColVw));
- MinMax(i, iMin) = dmin;
- MinMax(i, iMax) = dmax;
- } // end
- fprintf(fidlog, " log2po: %f \n", vec::meanSumMinMax(dsum, dmin, dmax, mhLogPostDens));
- fprintf(fidlog, " Minimum value.........:\n");;
- for (size_t i = 0; i < npar; ++i)
- fprintf(fidlog, " params: %lu : %f \n", i+1, MinMax(i, iMin));
- fprintf(fidlog, " log2po: %f \n", dmin);
- fprintf(fidlog, " Maximum value.........:\n");
- for (size_t i = 0; i < npar; ++i)
- fprintf(fidlog, " params: %lu : %f \n", i+1, MinMax(i, iMax));
- fprintf(fidlog, " log2po: %f \n", dmax);
- fprintf(fidlog, " \n");
- fclose(fidlog);
-
- jsux = 0;
- LastParametersRow = mat::get_row(mhParamDraws, currInitSizeArray-1); //x2(end,:);
- LastLogLiK(b-1) = mhLogPostDens(currInitSizeArray-1); //logpo2(end);
- InitSizeArray(b-1) = std::min((size_t) nruns(b-1)-j, MAX_nruns);
- // initialization of next file if necessary
- if (InitSizeArray(b-1))
- {
- NewFileVw(b-1)++; // = NewFile(b-1) + 1;
- irun = 1;
- } // end
- //irun++;
- } // end while % End of the simulations for one mh-block.
- //record.
- AcceptationRates(b-1) = sux/j;
- OpenOldFile[b] = 0;
- } // end % End of the loop over the mh-blocks.
-
- if (mexPutVariable("caller", "record_AcceptationRates", AcceptationRatesPtr))
- mexPrintf("MH Warning: due to error record_AcceptationRates is NOT set !! \n");
-
- if (mexPutVariable("caller", "record_LastParameters", mxLastParametersPtr))
- mexPrintf("MH Warning: due to error record_MhParamDraw is NOT set !! \n");
-
- if (mexPutVariable("caller", "record_LastLogLiK", mxLastLogLikPtr))
- mexPrintf("MH Warning: due to error record_LastLogLiK is NOT set !! \n");
-
- //NewFileVw = NewFile;
- if (mexPutVariable("caller", "NewFile", NewFileArrayPtr))
- mexPrintf("MH Warning: due to error NewFile is NOT set !! \n");
-
- // Cleanup
- mexPrintf("MH Cleanup !! \n");
-
- cleanup:
- if (mxMhLogPostDensPtr)
- mxDestroyArray(mxMhLogPostDensPtr); // delete log post density array
- if (mxMhParamDrawsPtr)
- mxDestroyArray(mxMhParamDrawsPtr); // delete accepted MCMC MH draws
-
-#ifdef MATLAB_MEX_FILE
- // Waitbar
- if (console_mode == 0)
- {
- // Bellow call to close waitbar seems to cause crashes and it is for
- // now left commented out and the waitbar neeeds to be closed manually
- // alternativelly, call with options_.console_mode=1;
- //mexCallMATLAB(0, NULL, 1, waitBarLhs, "close");
- //mxDestroyArray(waitBarLhs[0]);
- mxDestroyArray(waitBarRhs[1]);
- mxDestroyArray(waitBarRhs[0]);
- }
-#endif
-
- // return error code or last line run in the last MH block sub-array
- if (iret == 0)
- iret = (int) irun;
- return iret;
-
-}
-
-int
-logMCMCposterior(VectorConstView &estParams, const MatrixConstView &data,
- const size_t fblock, const size_t nBlocks, const VectorConstView &nMHruns, const MatrixConstView &D,
- VectorView &steadyState, VectorView &deepParams, MatrixView &Q, Matrix &H)
-{
- // Retrieve pointers to global variables
- const mxArray *M_ = mexGetVariablePtr("global", "M_");
- const mxArray *options_ = mexGetVariablePtr("global", "options_");
- const mxArray *estim_params_ = mexGetVariablePtr("global", "estim_params_");
-
- // Construct arguments of constructor of LogLikelihoodMain
- char *fName = mxArrayToString(mxGetField(M_, 0, "fname"));
- std::string resultsFileStem(fName);
- std::string dynamicDllFile(fName);
- mxFree(fName);
- dynamicDllFile += "_dynamic";
- dynamicDllFile += MEXEXT;
-
- size_t n_endo = (size_t) *mxGetPr(mxGetField(M_, 0, "endo_nbr"));
- size_t n_exo = (size_t) *mxGetPr(mxGetField(M_, 0, "exo_nbr"));
-
- size_t n_estParams = estParams.getSize();
-
- std::vector<size_t> zeta_fwrd, zeta_back, zeta_mixed, zeta_static;
- const mxArray *lli_mx = mxGetField(M_, 0, "lead_lag_incidence");
- MatrixConstView lli(mxGetPr(lli_mx), mxGetM(lli_mx), mxGetN(lli_mx), mxGetM(lli_mx));
- if (lli.getRows() != 3 || lli.getCols() != n_endo)
- throw LogMHMCMCposteriorMexErrMsgTxtException("Error in logMCMCposterior: Incorrect lead/lag incidence matrix");
- for (size_t i = 0; i < n_endo; i++)
- {
- if (lli(0, i) == 0 && lli(2, i) == 0)
- zeta_static.push_back(i);
- else if (lli(0, i) != 0 && lli(2, i) == 0)
- zeta_back.push_back(i);
- else if (lli(0, i) == 0 && lli(2, i) != 0)
- zeta_fwrd.push_back(i);
- else
- zeta_mixed.push_back(i);
- }
-
- double qz_criterium = *mxGetPr(mxGetField(options_, 0, "qz_criterium"));
- double lyapunov_tol = *mxGetPr(mxGetField(options_, 0, "lyapunov_complex_threshold"));
- double riccati_tol = *mxGetPr(mxGetField(options_, 0, "riccati_tol"));
- size_t presample = (size_t) *mxGetPr(mxGetField(options_, 0, "presample"));
- size_t console_mode = (size_t) *mxGetPr(mxGetField(options_, 0, "console_mode"));
- size_t load_mh_file = (size_t) *mxGetPr(mxGetField(options_, 0, "load_mh_file"));
-
- std::vector<size_t> varobs;
- const mxArray *varobs_mx = mxGetField(options_, 0, "varobs_id");
- if (mxGetM(varobs_mx) != 1)
- throw LogMHMCMCposteriorMexErrMsgTxtException("Error in logMCMCposterior: options_.varobs_id must be a row vector");
- size_t n_varobs = mxGetN(varobs_mx);
- std::transform(mxGetPr(varobs_mx), mxGetPr(varobs_mx) + n_varobs, back_inserter(varobs),
- std::bind2nd(std::minus<size_t>(), 1));
-
- if (data.getRows() != n_varobs)
- throw LogMHMCMCposteriorMexErrMsgTxtException("Error in logMCMCposterior: Data does not have as many rows as there are observed variables");
-
- std::vector<EstimationSubsample> estSubsamples;
- estSubsamples.push_back(EstimationSubsample(0, data.getCols() - 1));
-
- std::vector<EstimatedParameter> estParamsInfo;
- fillEstParamsInfo(mxGetField(estim_params_, 0, "var_exo"), EstimatedParameter::shock_SD,
- estParamsInfo);
- fillEstParamsInfo(mxGetField(estim_params_, 0, "var_endo"), EstimatedParameter::measureErr_SD,
- estParamsInfo);
- fillEstParamsInfo(mxGetField(estim_params_, 0, "corrx"), EstimatedParameter::shock_Corr,
- estParamsInfo);
- fillEstParamsInfo(mxGetField(estim_params_, 0, "corrn"), EstimatedParameter::measureErr_Corr,
- estParamsInfo);
- fillEstParamsInfo(mxGetField(estim_params_, 0, "param_vals"), EstimatedParameter::deepPar,
- estParamsInfo);
- EstimatedParametersDescription epd(estSubsamples, estParamsInfo);
-
- // Allocate LogPosteriorDensity object
- int info;
- LogPosteriorDensity lpd(dynamicDllFile, epd, n_endo, n_exo, zeta_fwrd, zeta_back, zeta_mixed, zeta_static,
- qz_criterium, varobs, riccati_tol, lyapunov_tol, info);
-
- // Construct MHMCMC Sampler
- RandomWalkMetropolisHastings rwmh(estParams.getSize());
- // Construct GaussianPrior drawDistribution m=0, sd=1
- GaussianPrior drawGaussDist01(0.0, 1.0, -INFINITY, INFINITY, 0.0, 1.0);
- // get Jscale = diag(bayestopt_.jscale);
- const mxArray *bayestopt_ = mexGetVariablePtr("global", "bayestopt_");
- const Matrix Jscale(n_estParams);
- const VectorConstView vJscale(mxGetPr(mxGetField(bayestopt_, 0, "jscale")), n_estParams, 1);
- Proposal pdd(vJscale, D);
-
- //sample MHMCMC draws and get get last line run in the last MH block sub-array
- int lastMHblockArrayLine = sampleMHMC(lpd, rwmh, steadyState, estParams, deepParams, data, Q, H, presample, info,
- nMHruns, fblock, nBlocks, pdd, epd, resultsFileStem, console_mode, load_mh_file);
-
- // Cleanups
- for (std::vector<EstimatedParameter>::iterator it = estParamsInfo.begin();
- it != estParamsInfo.end(); it++)
- delete it->prior;
-
- return lastMHblockArrayLine;
-}
-
-void
-mexFunction(int nlhs, mxArray *plhs[],
- int nrhs, const mxArray *prhs[])
-{
- if (nrhs != 10)
- DYN_MEX_FUNC_ERR_MSG_TXT("logposterior: exactly 11 arguments are required.");
- if (nlhs != 2)
- DYN_MEX_FUNC_ERR_MSG_TXT("logposterior: exactly two return arguments are required.");
-
- // Check and retrieve the arguments
-
- if (!mxIsDouble(prhs[0]) || mxGetN(prhs[0]) != 1)
- DYN_MEX_FUNC_ERR_MSG_TXT("logposterior: First argument must be a column vector of double-precision numbers");
-
- VectorConstView estParams(mxGetPr(prhs[0]), mxGetM(prhs[0]), 1);
-
- if (!mxIsDouble(prhs[1]))
- DYN_MEX_FUNC_ERR_MSG_TXT("logposterior: Second argument must be a matrix of double-precision numbers");
-
- size_t fblock = (size_t) mxGetScalar(prhs[2]);
- size_t nBlocks = (size_t) mxGetScalar(prhs[3]);
- VectorConstView nMHruns(mxGetPr(prhs[4]), mxGetM(prhs[4]), 1);
- MatrixConstView D(mxGetPr(prhs[5]), mxGetM(prhs[5]), mxGetN(prhs[5]), mxGetM(prhs[5]));
- const mxArray *dataset = prhs[6];
- const mxArray *options_ = prhs[7];
- const mxArray *M_ = prhs[8];
- const mxArray *bayestopt_ = prhs[9];
- const mxArray *oo_ = prhs[10];
-
- assert(nMHruns.getSize() == nBlocks);
-
- mxArray *dataset_data = mxGetField(dataset,0,"data");
- MatrixConstView data(mxGetPr(dataset_data), mxGetM(dataset_data), mxGetN(dataset_data), mxGetM(dataset_data));
-
- int endo_nbr = *(int*)mxGetPr(mxGetField(M_, 0, "endo_nbr"));
- int exo_nbr = *(int*)mxGetPr(mxGetField(M_, 0, "exo_nbr"));
- int param_nbr = *(int*)mxGetPr(mxGetField(M_, 0, "param_nbr"));
- int varobs_nbr = mxGetN(mxGetField(options_, 0, "varobs"));
-
- VectorView steadyState(mxGetPr(mxGetField(oo_,0,"steady_state")),endo_nbr, 1);
- VectorView deepParams(mxGetPr(mxGetField(M_, 0, "params")),param_nbr,1);
-
- MatrixView Q(mxGetPr(mxGetField(M_, 0, "Sigma_e")), exo_nbr, exo_nbr, exo_nbr);
-
- Matrix H(varobs_nbr,varobs_nbr);
- const mxArray *H_mx = mxGetField(M_, 0, "H");
- if (mxGetM(H_mx) == 1 && mxGetN(H_mx) == 1 && *mxGetPr(H_mx) == 0)
- H.setAll(0.0);
- else
- H = MatrixConstView(mxGetPr(H_mx), varobs_nbr, varobs_nbr, varobs_nbr);
-
- //calculate MHMCMC draws and get get last line run in the last MH block sub-array
- try
- {
- int lastMHblockArrayLine = logMCMCposterior(estParams, data, fblock, nBlocks, nMHruns, D, steadyState, deepParams, Q, H);
- plhs[1] = mxCreateDoubleMatrix(1, 1, mxREAL);
- *mxGetPr(plhs[1]) = (double) lastMHblockArrayLine;
- }
- catch (LogMHMCMCposteriorMexErrMsgTxtException e)
- {
- DYN_MEX_FUNC_ERR_MSG_TXT(e.getErrMsg());
- }
- plhs[0] = mxCreateDoubleScalar(0);
-}
diff --git a/mex/sources/estimation/logposterior.cc b/mex/sources/estimation/logposterior.cc
deleted file mode 100644
index 039a8cc5fd0733275f6218d4edf1125380f542bd..0000000000000000000000000000000000000000
--- a/mex/sources/estimation/logposterior.cc
+++ /dev/null
@@ -1,272 +0,0 @@
-/*
- * Copyright (C) 2010-2012 Dynare Team
- *
- * This file is part of Dynare.
- *
- * Dynare is free software: you can redistribute it and/or modify
- * it under the terms of the GNU General Public License as published by
- * the Free Software Foundation, either version 3 of the License, or
- * (at your option) any later version.
- *
- * Dynare is distributed in the hope that it will be useful,
- * but WITHOUT ANY WARRANTY; without even the implied warranty of
- * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
- * GNU General Public License for more details.
- *
- * You should have received a copy of the GNU General Public License
- * along with Dynare. If not, see <http://www.gnu.org/licenses/>.
- */
-
-#include <string>
-#include <vector>
-#include <algorithm>
-#include <functional>
-#include <sstream>
-
-#include "Vector.hh"
-#include "Matrix.hh"
-#include "LogPosteriorDensity.hh"
-
-#include <dynmex.h>
-
-class LogposteriorMexErrMsgTxtException
-{
-public:
- std::string errMsg;
- LogposteriorMexErrMsgTxtException(const std::string &msg) : errMsg(msg)
- {
- }
- inline const char *getErrMsg() { return errMsg.c_str(); }
-};
-
-void
-fillEstParamsInfo(const mxArray *bayestopt_, const mxArray *estim_params_info, EstimatedParameter::pType type,
- std::vector<EstimatedParameter> &estParamsInfo)
-{
- // execute once only
- static const mxArray *bayestopt_ubp = mxGetField(bayestopt_, 0, "ub"); // upper bound
- static const mxArray *bayestopt_lbp = mxGetField(bayestopt_, 0, "lb"); // lower bound
- static const mxArray *bayestopt_p1p = mxGetField(bayestopt_, 0, "p1"); // prior mean
- static const mxArray *bayestopt_p2p = mxGetField(bayestopt_, 0, "p2"); // prior standard deviation
- static const mxArray *bayestopt_p3p = mxGetField(bayestopt_, 0, "p3"); // lower bound
- static const mxArray *bayestopt_p4p = mxGetField(bayestopt_, 0, "p4"); // upper bound
- static const mxArray *bayestopt_p6p = mxGetField(bayestopt_, 0, "p6"); // first hyper-parameter (\alpha for the BETA and GAMMA distributions, s for the INVERSE GAMMAs, expectation for the GAUSSIAN distribution, lower bound for the UNIFORM distribution).
- static const mxArray *bayestopt_p7p = mxGetField(bayestopt_, 0, "p7"); // second hyper-parameter (\beta for the BETA and GAMMA distributions, \nu for the INVERSE GAMMAs, standard deviation for the GAUSSIAN distribution, upper bound for the UNIFORM distribution).
- static const mxArray *bayestopt_jscalep = mxGetField(bayestopt_, 0, "jscale"); // MCMC jump scale
-
- static const size_t bayestopt_size = mxGetM(bayestopt_);
- static const VectorConstView bayestopt_ub(mxGetPr(bayestopt_ubp), bayestopt_size, 1);
- static const VectorConstView bayestopt_lb(mxGetPr(bayestopt_lbp), bayestopt_size, 1);
- static const VectorConstView bayestopt_p1(mxGetPr(bayestopt_p1p), bayestopt_size, 1); //=mxGetField(bayestopt_, 0, "p1");
- static const VectorConstView bayestopt_p2(mxGetPr(bayestopt_p2p), bayestopt_size, 1); //=mxGetField(bayestopt_, 0, "p2");
- static const VectorConstView bayestopt_p3(mxGetPr(bayestopt_p3p), bayestopt_size, 1); //=mxGetField(bayestopt_, 0, "p3");
- static const VectorConstView bayestopt_p4(mxGetPr(bayestopt_p4p), bayestopt_size, 1); //=mxGetField(bayestopt_, 0, "p4");
- static const VectorConstView bayestopt_p6(mxGetPr(bayestopt_p6p), bayestopt_size, 1); //=mxGetField(bayestopt_, 0, "p6");
- static const VectorConstView bayestopt_p7(mxGetPr(bayestopt_p7p), bayestopt_size, 1); //=mxGetField(bayestopt_, 0, "p7");
- static const VectorConstView bayestopt_jscale(mxGetPr(bayestopt_jscalep), bayestopt_size, 1); //=mxGetField(bayestopt_, 0, "jscale");
-
- // loop processsing
- size_t m = mxGetM(estim_params_info), n = mxGetN(estim_params_info);
- MatrixConstView epi(mxGetPr(estim_params_info), m, n, m);
- size_t bayestopt_count = estParamsInfo.size();
-
- for (size_t i = 0; i < m; i++)
- {
- size_t col = 0;
- size_t id1 = (size_t) epi(i, col++) - 1;
- size_t id2 = 0;
- if (type == EstimatedParameter::shock_Corr
- || type == EstimatedParameter::measureErr_Corr)
- id2 = (size_t) epi(i, col++) - 1;
- col++; // Skip init_val #2 or #3
- double par_low_bound = bayestopt_lb(bayestopt_count); col++; //#3 epi(i, col++);
- double par_up_bound = bayestopt_ub(bayestopt_count); col++; //#4 epi(i, col++);
- Prior::pShape shape = (Prior::pShape) epi(i, col++);
- double mean = epi(i, col++);
- double std = epi(i, col++);
- double low_bound = bayestopt_p3(bayestopt_count);
- double up_bound = bayestopt_p4(bayestopt_count);
- double fhp = bayestopt_p6(bayestopt_count); // double p3 = epi(i, col++);
- double shp = bayestopt_p7(bayestopt_count); // double p4 = epi(i, col++);
-
- Prior *p = Prior::constructPrior(shape, mean, std, low_bound, up_bound, fhp, shp); //1.0,INFINITY);//p3, p4);
-
- // Only one subsample
- std::vector<size_t> subSampleIDs;
- subSampleIDs.push_back(0);
- estParamsInfo.push_back(EstimatedParameter(type, id1, id2, subSampleIDs,
- par_low_bound, par_up_bound, p));
- bayestopt_count++;
- }
-}
-
-template <class VEC1, class VEC2>
-double
-logposterior(VEC1 &estParams, const MatrixConstView &data,
- const mxArray *options_, const mxArray *M_, const mxArray *estim_params_,
- const mxArray *bayestopt_, const mxArray *oo_, VEC2 &steadyState, double *trend_coeff,
- int &info, VectorView &deepParams, Matrix &H, MatrixView &Q)
-{
- // Construct arguments of constructor of LogLikelihoodMain
- char *fName = mxArrayToString(mxGetField(M_, 0, "fname"));
- std::string dynamicDllFile(fName);
- mxFree(fName);
- dynamicDllFile += "_dynamic";
- dynamicDllFile += MEXEXT;
-
- size_t n_endo = (size_t) *mxGetPr(mxGetField(M_, 0, "endo_nbr"));
- size_t n_exo = (size_t) *mxGetPr(mxGetField(M_, 0, "exo_nbr"));
- size_t n_param = (size_t) *mxGetPr(mxGetField(M_, 0, "param_nbr"));
- size_t n_estParams = estParams.getSize();
-
- std::vector<size_t> zeta_fwrd, zeta_back, zeta_mixed, zeta_static;
- const mxArray *lli_mx = mxGetField(M_, 0, "lead_lag_incidence");
- MatrixConstView lli(mxGetPr(lli_mx), mxGetM(lli_mx), mxGetN(lli_mx), mxGetM(lli_mx));
- if (lli.getRows() != 3 || lli.getCols() != n_endo)
- throw LogposteriorMexErrMsgTxtException("Incorrect lead/lag incidence matrix");
-
- for (size_t i = 0; i < n_endo; i++)
- {
- if (lli(0, i) == 0 && lli(2, i) == 0)
- zeta_static.push_back(i);
- else if (lli(0, i) != 0 && lli(2, i) == 0)
- zeta_back.push_back(i);
- else if (lli(0, i) == 0 && lli(2, i) != 0)
- zeta_fwrd.push_back(i);
- else
- zeta_mixed.push_back(i);
- }
-
- double qz_criterium = *mxGetPr(mxGetField(options_, 0, "qz_criterium"));
- double lyapunov_tol = *mxGetPr(mxGetField(options_, 0, "lyapunov_complex_threshold"));
- double riccati_tol = *mxGetPr(mxGetField(options_, 0, "riccati_tol"));
- size_t presample = (size_t) *mxGetPr(mxGetField(options_, 0, "presample"));
-
- std::vector<size_t> varobs;
- const mxArray *varobs_mx = mxGetField(options_, 0, "varobs_id");
- if (mxGetM(varobs_mx) != 1)
- throw LogposteriorMexErrMsgTxtException("options_.varobs_id must be a row vector");
-
- size_t n_varobs = mxGetN(varobs_mx);
- // substract 1.0 from obsverved variables index
- std::transform(mxGetPr(varobs_mx), mxGetPr(varobs_mx) + n_varobs, back_inserter(varobs),
- std::bind2nd(std::minus<size_t>(), 1));
-
- if (data.getRows() != n_varobs)
- throw LogposteriorMexErrMsgTxtException("Data does not have as many rows as there are observed variables");
-
- std::vector<EstimationSubsample> estSubsamples;
- estSubsamples.push_back(EstimationSubsample(0, data.getCols() - 1));
-
- std::vector<EstimatedParameter> estParamsInfo;
- fillEstParamsInfo(bayestopt_, mxGetField(estim_params_, 0, "var_exo"), EstimatedParameter::shock_SD,
- estParamsInfo);
- fillEstParamsInfo(bayestopt_, mxGetField(estim_params_, 0, "var_endo"), EstimatedParameter::measureErr_SD,
- estParamsInfo);
- fillEstParamsInfo(bayestopt_, mxGetField(estim_params_, 0, "corrx"), EstimatedParameter::shock_Corr,
- estParamsInfo);
- fillEstParamsInfo(bayestopt_, mxGetField(estim_params_, 0, "corrn"), EstimatedParameter::measureErr_Corr,
- estParamsInfo);
- fillEstParamsInfo(bayestopt_, mxGetField(estim_params_, 0, "param_vals"), EstimatedParameter::deepPar,
- estParamsInfo);
-
- EstimatedParametersDescription epd(estSubsamples, estParamsInfo);
-
- // Allocate LogPosteriorDensity object
- LogPosteriorDensity lpd(dynamicDllFile, epd, n_endo, n_exo, zeta_fwrd, zeta_back, zeta_mixed, zeta_static,
- qz_criterium, varobs, riccati_tol, lyapunov_tol, info);
-
- // Construct arguments of compute() method
-
- // Compute the posterior
- double logPD = lpd.compute(steadyState, estParams, deepParams, data, Q, H, presample, info);
-
- // Cleanups
- for (std::vector<EstimatedParameter>::iterator it = estParamsInfo.begin();
- it != estParamsInfo.end(); it++)
- delete it->prior;
-
- return logPD;
-}
-
-void
-mexFunction(int nlhs, mxArray *plhs[],
- int nrhs, const mxArray *prhs[])
-{
- if (nrhs != 7 )
- DYN_MEX_FUNC_ERR_MSG_TXT("logposterior: exactly 7 input arguments are required.");
-
- if (nlhs > 9 )
- DYN_MEX_FUNC_ERR_MSG_TXT("logposterior returns 8 output arguments at the most.");
-
- // Check and retrieve the RHS arguments
-
- if (!mxIsDouble(prhs[0]) || mxGetN(prhs[0]) != 1)
- DYN_MEX_FUNC_ERR_MSG_TXT("logposterior: First argument must be a column vector of double-precision numbers");
-
- VectorConstView estParams(mxGetPr(prhs[0]), mxGetM(prhs[0]), 1);
-
- for (int i = 1; i < 7; ++i)
- if (!mxIsStruct(prhs[i]))
- {
- std::stringstream msg;
- msg << "logposterior: argument " << i+1 << " must be a Matlab structure";
- DYN_MEX_FUNC_ERR_MSG_TXT(msg.str().c_str());
- }
-
- const mxArray *dataset = prhs[1];
- const mxArray *options_ = prhs[2];
- const mxArray *M_ = prhs[3];
- const mxArray *estim_params_ = prhs[4];
- const mxArray *bayestopt_ = prhs[5];
- const mxArray *oo_ = prhs[6];
-
- mxArray *dataset_data = mxGetField(dataset,0,"data");
- MatrixConstView data(mxGetPr(dataset_data), mxGetM(dataset_data), mxGetN(dataset_data), mxGetM(dataset_data));
-
- // Creaete LHS arguments
-
- size_t endo_nbr = (size_t) *mxGetPr(mxGetField(M_, 0, "endo_nbr"));
- size_t exo_nbr = (size_t) *mxGetPr(mxGetField(M_, 0, "exo_nbr"));
- size_t param_nbr = (size_t) *mxGetPr(mxGetField(M_, 0, "param_nbr"));
- size_t varobs_nbr = mxGetM(mxGetField(options_, 0, "varobs"));
- plhs[0] = mxCreateDoubleMatrix(1, 1, mxREAL);
- plhs[1] = mxCreateDoubleMatrix(1, 1, mxREAL);
- plhs[2] = mxCreateDoubleMatrix(endo_nbr, 1, mxREAL);
- plhs[3] = mxCreateDoubleMatrix(varobs_nbr, 1, mxREAL);
- plhs[4] = mxCreateDoubleMatrix(1, 1, mxREAL);
- plhs[5] = mxCreateDoubleMatrix(param_nbr, 1, mxREAL);
- plhs[6] = mxCreateDoubleMatrix(varobs_nbr, varobs_nbr, mxREAL);
- plhs[7] = mxCreateDoubleMatrix(exo_nbr, exo_nbr, mxREAL);
- double *lik = mxGetPr(plhs[0]);
- double *exit_flag = mxGetPr(plhs[1]);
-
- VectorView steadyState(mxGetPr(mxGetField(oo_,0,"steady_state")),endo_nbr, 1);
- VectorView deepParams(mxGetPr(mxGetField(M_, 0, "params")),param_nbr,1);
-
- MatrixView Q(mxGetPr(mxGetField(M_, 0, "Sigma_e")), exo_nbr, exo_nbr, exo_nbr);
-
- Matrix H(varobs_nbr,varobs_nbr);
- const mxArray *H_mx = mxGetField(M_, 0, "H");
- if (mxGetM(H_mx) == 1 && mxGetN(H_mx) == 1 && *mxGetPr(H_mx) == 0)
- H.setAll(0.0);
- else
- H = MatrixConstView(mxGetPr(H_mx), varobs_nbr, varobs_nbr, varobs_nbr);
-
- double *trend_coeff = mxGetPr(plhs[3]);
- double *info_mx = mxGetPr(plhs[4]);
-
- // Compute and return the value
- try
- {
- int info;
- *lik = logposterior(estParams, data, options_, M_, estim_params_, bayestopt_, oo_,
- steadyState, trend_coeff, info, deepParams, H, Q);
- *info_mx = info;
- *exit_flag = info;
- }
- catch (LogposteriorMexErrMsgTxtException e)
- {
- DYN_MEX_FUNC_ERR_MSG_TXT(e.getErrMsg());
- }
-}
diff --git a/mex/sources/estimation/tests/DsgeLikelihood.m b/mex/sources/estimation/tests/DsgeLikelihood.m
deleted file mode 100644
index 6de151c6d82ac409c138fd174e7ccbdb2421cf66..0000000000000000000000000000000000000000
--- a/mex/sources/estimation/tests/DsgeLikelihood.m
+++ /dev/null
@@ -1,345 +0,0 @@
-function [fval,cost_flag,ys,trend_coeff,info] = DsgeLikelihood(xparam1,gend,data,data_index,number_of_observations,no_more_missing_observations)
-% function [fval,cost_flag,ys,trend_coeff,info] = DsgeLikelihood(xparam1,gend,data,data_index,number_of_observations,no_more_missing_observations)
-% Evaluates the posterior kernel of a dsge model.
-%
-% INPUTS
-% xparam1 [double] vector of model parameters.
-% gend [integer] scalar specifying the number of observations.
-% data [double] matrix of data
-% data_index [cell] cell of column vectors
-% number_of_observations [integer]
-% no_more_missing_observations [integer]
-% OUTPUTS
-% fval : value of the posterior kernel at xparam1.
-% cost_flag : zero if the function returns a penalty, one otherwise.
-% ys : steady state of original endogenous variables
-% trend_coeff :
-% info : vector of informations about the penalty:
-% 41: one (many) parameter(s) do(es) not satisfied the lower bound
-% 42: one (many) parameter(s) do(es) not satisfied the upper bound
-%
-% SPECIAL REQUIREMENTS
-%
-
-% Copyright (C) 2004-2010 Dynare Team
-%
-% This file is part of Dynare.
-%
-% Dynare is free software: you can redistribute it and/or modify
-% it under the terms of the GNU General Public License as published by
-% the Free Software Foundation, either version 3 of the License, or
-% (at your option) any later version.
-%
-% Dynare is distributed in the hope that it will be useful,
-% but WITHOUT ANY WARRANTY; without even the implied warranty of
-% MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
-% GNU General Public License for more details.
-%
-% You should have received a copy of the GNU General Public License
-% along with Dynare. If not, see <http://www.gnu.org/licenses/>.
-
-global bayestopt_ estim_params_ options_ trend_coeff_ M_ oo_
-fval = [];
-ys = [];
-trend_coeff = [];
-cost_flag = 1;
-nobs = size(options_.varobs,1);
-%------------------------------------------------------------------------------
-% 1. Get the structural parameters & define penalties
-%------------------------------------------------------------------------------
-if options_.mode_compute ~= 1 & any(xparam1 < bayestopt_.lb)
- k = find(xparam1 < bayestopt_.lb);
- fval = bayestopt_.penalty+sum((bayestopt_.lb(k)-xparam1(k)).^2);
- cost_flag = 0;
- info = 41;
- return;
-end
-if options_.mode_compute ~= 1 & any(xparam1 > bayestopt_.ub)
- k = find(xparam1 > bayestopt_.ub);
- fval = bayestopt_.penalty+sum((xparam1(k)-bayestopt_.ub(k)).^2);
- cost_flag = 0;
- info = 42;
- return;
-end
-Q = M_.Sigma_e;
-H = M_.H;
-for i=1:estim_params_.nvx
- k =estim_params_.var_exo(i,1);
- Q(k,k) = xparam1(i)*xparam1(i);
-end
-offset = estim_params_.nvx;
-if estim_params_.nvn
- for i=1:estim_params_.nvn
- k = estim_params_.var_endo(i,1);
- H(k,k) = xparam1(i+offset)*xparam1(i+offset);
- end
- offset = offset+estim_params_.nvn;
-end
-if estim_params_.ncx
- for i=1:estim_params_.ncx
- k1 =estim_params_.corrx(i,1);
- k2 =estim_params_.corrx(i,2);
- Q(k1,k2) = xparam1(i+offset)*sqrt(Q(k1,k1)*Q(k2,k2));
- Q(k2,k1) = Q(k1,k2);
- end
- [CholQ,testQ] = chol(Q);
- if testQ %% The variance-covariance matrix of the structural innovations is not definite positive.
- %% We have to compute the eigenvalues of this matrix in order to build the penalty.
- a = diag(eig(Q));
- k = find(a < 0);
- if k > 0
- fval = bayestopt_.penalty+sum(-a(k));
- cost_flag = 0;
- info = 43;
- return
- end
- end
- offset = offset+estim_params_.ncx;
-end
-if estim_params_.ncn
- for i=1:estim_params_.ncn
- k1 = options_.lgyidx2varobs(estim_params_.corrn(i,1));
- k2 = options_.lgyidx2varobs(estim_params_.corrn(i,2));
- H(k1,k2) = xparam1(i+offset)*sqrt(H(k1,k1)*H(k2,k2));
- H(k2,k1) = H(k1,k2);
- end
- [CholH,testH] = chol(H);
- if testH
- a = diag(eig(H));
- k = find(a < 0);
- if k > 0
- fval = bayestopt_.penalty+sum(-a(k));
- cost_flag = 0;
- info = 44;
- return
- end
- end
- offset = offset+estim_params_.ncn;
-end
-if estim_params_.np > 0
- M_.params(estim_params_.param_vals(:,1)) = xparam1(offset+1:end);
-end
-M_.Sigma_e = Q;
-M_.H = H;
-%------------------------------------------------------------------------------
-% 2. call model setup & reduction program
-%------------------------------------------------------------------------------
-[T,R,SteadyState,info] = dynare_resolve(bayestopt_.restrict_var_list,...
- bayestopt_.restrict_columns,...
- bayestopt_.restrict_aux);
-if info(1) == 1 || info(1) == 2 || info(1) == 5
- fval = bayestopt_.penalty+1;
- cost_flag = 0;
- return
-elseif info(1) == 3 || info(1) == 4 || info(1)==6 ||info(1) == 19 || info(1) == 20 || info(1) == 21
- fval = bayestopt_.penalty+info(2);
- cost_flag = 0;
- return
-end
-bayestopt_.mf = bayestopt_.mf1;
-if options_.noconstant
- constant = zeros(nobs,1);
-else
- if options_.loglinear
- constant = log(SteadyState(bayestopt_.mfys));
- else
- constant = SteadyState(bayestopt_.mfys);
- end
-end
-if bayestopt_.with_trend
- trend_coeff = zeros(nobs,1);
- t = options_.trend_coeffs;
- for i=1:length(t)
- if ~isempty(t{i})
- trend_coeff(i) = evalin('base',t{i});
- end
- end
- trend = repmat(constant,1,gend)+trend_coeff*[1:gend];
-else
- trend = repmat(constant,1,gend);
-end
-start = options_.presample+1;
-np = size(T,1);
-mf = bayestopt_.mf;
-no_missing_data_flag = (number_of_observations==gend*nobs);
-%------------------------------------------------------------------------------
-% 3. Initial condition of the Kalman filter
-%------------------------------------------------------------------------------
-T
-R
-Q
-R*Q*R'
-pause
-options_.lik_init = 1;
-kalman_algo = options_.kalman_algo;
-if options_.lik_init == 1 % Kalman filter
- if kalman_algo ~= 2
- kalman_algo = 1;
- end
- Pstar = lyapunov_symm(T,R*Q*R',options_.qz_criterium,options_.lyapunov_complex_threshold);
- Pinf = [];
-elseif options_.lik_init == 2 % Old Diffuse Kalman filter
- if kalman_algo ~= 2
- kalman_algo = 1;
- end
- Pstar = options_.Harvey_scale_factor*eye(np);
- Pinf = [];
-elseif options_.lik_init == 3 % Diffuse Kalman filter
- if kalman_algo ~= 4
- kalman_algo = 3;
- end
- [QT,ST] = schur(T);
- e1 = abs(ordeig(ST)) > 2-options_.qz_criterium;
- [QT,ST] = ordschur(QT,ST,e1);
- k = find(abs(ordeig(ST)) > 2-options_.qz_criterium);
- nk = length(k);
- nk1 = nk+1;
- Pinf = zeros(np,np);
- Pinf(1:nk,1:nk) = eye(nk);
- Pstar = zeros(np,np);
- B = QT'*R*Q*R'*QT;
- for i=np:-1:nk+2
- if ST(i,i-1) == 0
- if i == np
- c = zeros(np-nk,1);
- else
- c = ST(nk1:i,:)*(Pstar(:,i+1:end)*ST(i,i+1:end)')+...
- ST(i,i)*ST(nk1:i,i+1:end)*Pstar(i+1:end,i);
- end
- q = eye(i-nk)-ST(nk1:i,nk1:i)*ST(i,i);
- Pstar(nk1:i,i) = q\(B(nk1:i,i)+c);
- Pstar(i,nk1:i-1) = Pstar(nk1:i-1,i)';
- else
- if i == np
- c = zeros(np-nk,1);
- c1 = zeros(np-nk,1);
- else
- c = ST(nk1:i,:)*(Pstar(:,i+1:end)*ST(i,i+1:end)')+...
- ST(i,i)*ST(nk1:i,i+1:end)*Pstar(i+1:end,i)+...
- ST(i,i-1)*ST(nk1:i,i+1:end)*Pstar(i+1:end,i-1);
- c1 = ST(nk1:i,:)*(Pstar(:,i+1:end)*ST(i-1,i+1:end)')+...
- ST(i-1,i-1)*ST(nk1:i,i+1:end)*Pstar(i+1:end,i-1)+...
- ST(i-1,i)*ST(nk1:i,i+1:end)*Pstar(i+1:end,i);
- end
- q = [eye(i-nk)-ST(nk1:i,nk1:i)*ST(i,i) -ST(nk1:i,nk1:i)*ST(i,i-1);...
- -ST(nk1:i,nk1:i)*ST(i-1,i) eye(i-nk)-ST(nk1:i,nk1:i)*ST(i-1,i-1)];
- z = q\[B(nk1:i,i)+c;B(nk1:i,i-1)+c1];
- Pstar(nk1:i,i) = z(1:(i-nk));
- Pstar(nk1:i,i-1) = z(i-nk+1:end);
- Pstar(i,nk1:i-1) = Pstar(nk1:i-1,i)';
- Pstar(i-1,nk1:i-2) = Pstar(nk1:i-2,i-1)';
- i = i - 1;
- end
- end
- if i == nk+2
- c = ST(nk+1,:)*(Pstar(:,nk+2:end)*ST(nk1,nk+2:end)')+ST(nk1,nk1)*ST(nk1,nk+2:end)*Pstar(nk+2:end,nk1);
- Pstar(nk1,nk1)=(B(nk1,nk1)+c)/(1-ST(nk1,nk1)*ST(nk1,nk1));
- end
- Z = QT(mf,:);
- R1 = QT'*R;
- [QQ,RR,EE] = qr(Z*ST(:,1:nk),0);
- k = find(abs(diag([RR; zeros(nk-size(Z,1),size(RR,2))])) < 1e-8);
- if length(k) > 0
- k1 = EE(:,k);
- dd =ones(nk,1);
- dd(k1) = zeros(length(k1),1);
- Pinf(1:nk,1:nk) = diag(dd);
- end
-end
-if kalman_algo == 2
-end
-kalman_tol = options_.kalman_tol;
-riccati_tol = options_.riccati_tol;
-mf = bayestopt_.mf1;
-Y = data-trend;
-Pstar
-pause
-%------------------------------------------------------------------------------
-% 4. Likelihood evaluation
-%------------------------------------------------------------------------------
-if (kalman_algo==1)% Multivariate Kalman Filter
- if no_missing_data_flag
- LIK = kalman_filter(T,R,Q,H,Pstar,Y,start,mf,kalman_tol,riccati_tol);
- else
- LIK = ...
- missing_observations_kalman_filter(T,R,Q,H,Pstar,Y,start,mf,kalman_tol,riccati_tol, ...
- data_index,number_of_observations,no_more_missing_observations);
- end
- if isinf(LIK)
- kalman_algo = 2;
- end
-end
-if (kalman_algo==2)% Univariate Kalman Filter
- no_correlation_flag = 1;
- if length(H)==1 & H == 0
- H = zeros(nobs,1);
- else
- if all(all(abs(H-diag(diag(H)))<1e-14))% ie, the covariance matrix is diagonal...
- H = diag(H);
- else
- no_correlation_flag = 0;
- end
- end
- if no_correlation_flag
- LIK = univariate_kalman_filter(T,R,Q,H,Pstar,Y,start,mf,kalman_tol,riccati_tol,data_index,number_of_observations,no_more_missing_observations);
- else
- LIK = univariate_kalman_filter_corr(T,R,Q,H,Pstar,Y,start,mf,kalman_tol,riccati_tol,data_index,number_of_observations,no_more_missing_observations);
- end
-end
-if (kalman_algo==3)% Multivariate Diffuse Kalman Filter
- if no_missing_data_flag
- LIK = diffuse_kalman_filter(ST,R1,Q,H,Pinf,Pstar,Y,start,Z,kalman_tol, ...
- riccati_tol);
- else
- LIK = missing_observations_diffuse_kalman_filter(ST,R1,Q,H,Pinf, ...
- Pstar,Y,start,Z,kalman_tol,riccati_tol,...
- data_index,number_of_observations,...
- no_more_missing_observations);
- end
- if isinf(LIK)
- kalman_algo = 4;
- end
-end
-if (kalman_algo==4)% Univariate Diffuse Kalman Filter
- no_correlation_flag = 1;
- if length(H)==1 & H == 0
- H = zeros(nobs,1);
- else
- if all(all(abs(H-diag(diag(H)))<1e-14))% ie, the covariance matrix is diagonal...
- H = diag(H);
- else
- no_correlation_flag = 0;
- end
- end
- if no_correlation_flag
- LIK = univariate_diffuse_kalman_filter(ST,R1,Q,H,Pinf,Pstar,Y, ...
- start,Z,kalman_tol,riccati_tol,data_index,...
- number_of_observations,no_more_missing_observations);
- else
- LIK = univariate_diffuse_kalman_filter_corr(ST,R1,Q,H,Pinf,Pstar, ...
- Y,start,Z,kalman_tol,riccati_tol,...
- data_index,number_of_observations,...
- no_more_missing_observations);
- end
-end
-if isnan(LIK)
- cost_flag = 0;
- return
-end
-if imag(LIK)~=0
- likelihood = bayestopt_.penalty;
-else
- likelihood = LIK;
-end
-% ------------------------------------------------------------------------------
-% Adds prior if necessary
-% ------------------------------------------------------------------------------
-lnprior = priordens(xparam1,bayestopt_.pshape,bayestopt_.p6,bayestopt_.p7,bayestopt_.p3,bayestopt_.p4);
-fval = (likelihood-lnprior);
-likelihood
-lnprior
-fval
-pause
-LIKDLL=logposterior(xparam1,Y,mexext)
-pause
-options_.kalman_algo = kalman_algo;
diff --git a/mex/sources/estimation/tests/Makefile.am b/mex/sources/estimation/tests/Makefile.am
deleted file mode 100644
index 8ba8b7a84fea082846799f27c2e5d49504632826..0000000000000000000000000000000000000000
--- a/mex/sources/estimation/tests/Makefile.am
+++ /dev/null
@@ -1,24 +0,0 @@
-check_PROGRAMS = test-dr testModelSolution testInitKalman testKalman testPDF
-
-test_dr_SOURCES = ../libmat/Matrix.cc ../libmat/Vector.cc ../libmat/QRDecomposition.cc ../libmat/GeneralizedSchurDecomposition.cc ../libmat/LUSolver.cc ../DecisionRules.cc test-dr.cc
-test_dr_LDADD = $(LAPACK_LIBS) $(BLAS_LIBS) $(LIBS) $(FLIBS)
-test_dr_CPPFLAGS = -I.. -I../libmat -I../../
-
-testModelSolution_SOURCES = ../libmat/Matrix.cc ../libmat/Vector.cc ../libmat/QRDecomposition.cc ../libmat/GeneralizedSchurDecomposition.cc ../libmat/LUSolver.cc ../utils/dynamic_dll.cc ../DecisionRules.cc ../ModelSolution.cc testModelSolution.cc
-testModelSolution_LDADD = $(LAPACK_LIBS) $(BLAS_LIBS) $(LIBS) $(FLIBS) $(LIBADD_DLOPEN)
-testModelSolution_CPPFLAGS = -I.. -I../libmat -I../../ -I../utils
-
-testInitKalman_SOURCES = ../libmat/Matrix.cc ../libmat/Vector.cc ../libmat/QRDecomposition.cc ../libmat/GeneralizedSchurDecomposition.cc ../libmat/LUSolver.cc ../utils/dynamic_dll.cc ../DecisionRules.cc ../ModelSolution.cc ../InitializeKalmanFilter.cc ../DetrendData.cc testInitKalman.cc
-testInitKalman_LDADD = $(LAPACK_LIBS) $(BLAS_LIBS) $(LIBS) $(FLIBS) $(LIBADD_DLOPEN)
-testInitKalman_CPPFLAGS = -I.. -I../libmat -I../../ -I../utils
-
-testKalman_SOURCES = ../libmat/Matrix.cc ../libmat/Vector.cc ../libmat/QRDecomposition.cc ../libmat/GeneralizedSchurDecomposition.cc ../libmat/LUSolver.cc ../utils/dynamic_dll.cc ../DecisionRules.cc ../ModelSolution.cc ../InitializeKalmanFilter.cc ../DetrendData.cc ../KalmanFilter.cc testKalman.cc
-testKalman_LDADD = $(LAPACK_LIBS) $(BLAS_LIBS) $(LIBS) $(FLIBS) $(LIBADD_DLOPEN)
-testKalman_CPPFLAGS = -I.. -I../libmat -I../../ -I../utils
-
-testPDF_SOURCES = ../Prior.cc ../Prior.hh testPDF.cc
-testPDF_CPPFLAGS = -I..
-
-check-local:
- ./test-dr
- ./testPDF
diff --git a/mex/sources/estimation/tests/fs2000k2e.mod b/mex/sources/estimation/tests/fs2000k2e.mod
deleted file mode 100644
index 88cb3136fefd3be988df399e2a224d9b6ca1c4e6..0000000000000000000000000000000000000000
--- a/mex/sources/estimation/tests/fs2000k2e.mod
+++ /dev/null
@@ -1,77 +0,0 @@
-/* Checks that, for order = 2, k_order_solver = 0 (fs2000k2a)
- and k_order_solver = 1 (this file) give the same results */
-
-var m P c e W R k d n l gy_obs gp_obs y dA ;
-varexo e_a e_m;
-
-parameters alp bet gam mst rho psi del;
-
-alp = 0.33;
-bet = 0.99;
-gam = 0.003;
-mst = 1.011;
-rho = 0.7;
-psi = 0.787;
-del = 0.02;
-
-model (use_dll);
-dA = exp(gam+e_a);
-log(m) = (1-rho)*log(mst) + rho*log(m(-1))+e_m;
--P/(c(+1)*P(+1)*m)+bet*P(+1)*(alp*exp(-alp*(gam+log(e(+1))))*k^(alp-1)*n(+1)^(1-alp)+(1-del)*exp(-(gam+log(e(+1)))))/(c(+2)*P(+2)*m(+1))=0;
-W = l/n;
--(psi/(1-psi))*(c*P/(1-n))+l/n = 0;
-R = P*(1-alp)*exp(-alp*(gam+e_a))*k(-1)^alp*n^(-alp)/W;
-1/(c*P)-bet*P*(1-alp)*exp(-alp*(gam+e_a))*k(-1)^alp*n^(1-alp)/(m*l*c(+1)*P(+1)) = 0;
-c+k = exp(-alp*(gam+e_a))*k(-1)^alp*n^(1-alp)+(1-del)*exp(-(gam+e_a))*k(-1);
-P*c = m;
-m-1+d = l;
-e = exp(e_a);
-y = k(-1)^alp*n^(1-alp)*exp(-alp*(gam+e_a));
-gy_obs = dA*y/y(-1);
-gp_obs = (P/P(-1))*m(-1)/dA;
-end;
-
-initval;
-m = mst;
-P = 2.25;
-c = 0.45;
-e = 1;
-W = 4;
-R = 1.02;
-k = 6;
-d = 0.85;
-n = 0.19;
-l = 0.86;
-y = 0.6;
-gy_obs = exp(gam);
-gp_obs = exp(-gam);
-dA = exp(gam);
-end;
-
-shocks;
-var e_a; stderr 0.014;
-var e_m; stderr 0.005;
-end;
-
-steady;
-
-
-estimated_params;
-alp, beta_pdf, 0.356, 0.02;
-bet, beta_pdf, 0.993, 0.002;
-gam, normal_pdf, 0.0085, 0.003;
-mst, normal_pdf, 1.0002, 0.007;
-rho, beta_pdf, 0.129, 0.223;
-psi, beta_pdf, 0.65, 0.05;
-del, beta_pdf, 0.01, 0.005;
-stderr e_a, inv_gamma_pdf, 0.035449, inf;
-stderr e_m, inv_gamma_pdf, 0.008862, inf;
-end;
-
-varobs gp_obs gy_obs;
-
-//estimation(datafile=fsdat,nobs=192,loglinear,mh_replic=2000,
-// mode_compute=4,mh_nblocks=2,mh_drop=0.45,mh_jscale=0.65);
-estimation(datafile=fsdat,nobs=192,mh_replic=2000,
- mode_compute=4,mh_nblocks=2,mh_drop=0.45,mh_jscale=0.65);
-
diff --git a/mex/sources/estimation/tests/logposterior_dll_test/random_walk_metropolis_hastings_core.m b/mex/sources/estimation/tests/logposterior_dll_test/random_walk_metropolis_hastings_core.m
deleted file mode 100644
index 9e741fa7f7cdf6763754338f700c61d760a08d87..0000000000000000000000000000000000000000
--- a/mex/sources/estimation/tests/logposterior_dll_test/random_walk_metropolis_hastings_core.m
+++ /dev/null
@@ -1,285 +0,0 @@
-function myoutput = random_walk_metropolis_hastings_core(myinputs,fblck,nblck,whoiam, ThisMatlab)
-% PARALLEL CONTEXT
-% This function contain the most computationally intensive portion of code in
-% random_walk_metropolis_hastings (the 'for xxx = fblck:nblck' loop). The branches in 'for'
-% cycle and are completely independent than suitable to be executed in parallel way.
-%
-% INPUTS
-% o myimput [struc] The mandatory variables for local/remote
-% parallel computing obtained from random_walk_metropolis_hastings.m
-% function.
-% o fblck and nblck [integer] The Metropolis-Hastings chains.
-% o whoiam [integer] In concurrent programming a modality to refer to the differents thread running in parallel is needed.
-% The integer whoaim is the integer that
-% allows us to distinguish between them. Then it is the index number of this CPU among all CPUs in the
-% cluster.
-% o ThisMatlab [integer] Allows us to distinguish between the
-% 'main' matlab, the slave matlab worker, local matlab, remote matlab,
-% ... Then it is the index number of this slave machine in the cluster.
-% OUTPUTS
-% o myoutput [struc]
-% If executed without parallel is the original output of 'for b =
-% fblck:nblck' otherwise a portion of it computed on a specific core or
-% remote machine. In this case:
-% record;
-% irun;
-% NewFile;
-% OutputFileName
-%
-% ALGORITHM
-% Portion of Metropolis-Hastings.
-%
-% SPECIAL REQUIREMENTS.
-% None.
-
-% PARALLEL CONTEXT
-% The most computationally intensive part of this function may be executed
-% in parallel. The code sutable to be executed in parallel on multi core or cluster machine,
-% is removed from this function and placed in random_walk_metropolis_hastings_core.m funtion.
-% Then the DYNARE parallel package contain a set of pairs matlab functios that can be executed in
-% parallel and called name_function.m and name_function_core.m.
-% In addition in the parallel package we have second set of functions used
-% to manage the parallel computation.
-%
-% This function was the first function to be parallelized, later other
-% functions have been parallelized using the same methodology.
-% Then the comments write here can be used for all the other pairs of
-% parallel functions and also for management funtions.
-
-
-% Copyright (C) 2006-2010 Dynare Team
-%
-% This file is part of Dynare.
-%
-% Dynare is free software: you can redistribute it and/or modify
-% it under the terms of the GNU General Public License as published by
-% the Free Software Foundation, either version 3 of the License, or
-% (at your option) any later version.
-%
-% Dynare is distributed in the hope that it will be useful,
-% but WITHOUT ANY WARRANTY; without even the implied warranty of
-% MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
-% GNU General Public License for more details.
-%
-% You should have received a copy of the GNU General Public License
-% along with Dynare. If not, see <http://www.gnu.org/licenses/>.
-
-if nargin<4,
- whoiam=0;
-end
-
-
-global bayestopt_ estim_params_ options_ M_ oo_
-
-% reshape 'myinputs' for local computation.
-% In order to avoid confusion in the name space, the instruction struct2local(myinputs) is replaced by:
-
-TargetFun=myinputs.TargetFun;
-ProposalFun=myinputs.ProposalFun;
-xparam1=myinputs.xparam1;
-vv=myinputs.vv;
-mh_bounds=myinputs.mh_bounds;
-ix2=myinputs.ix2;
-ilogpo2=myinputs.ilogpo2;
-ModelName=myinputs.ModelName;
-fline=myinputs.fline;
-npar=myinputs.npar;
-nruns=myinputs.nruns;
-NewFile=myinputs.NewFile;
-MAX_nruns=myinputs.MAX_nruns;
-d=myinputs.d;
-InitSizeArray=myinputs.InitSizeArray;
-record=myinputs.record;
-varargin=myinputs.varargin;
-
-% Necessary only for remote computing!
-if whoiam
- Parallel=myinputs.Parallel;
- % initialize persistent variables in priordens()
- priordens(xparam1,bayestopt_.pshape,bayestopt_.p6,bayestopt_.p7, ...
- bayestopt_.p3,bayestopt_.p4,1);
-end
-
-% (re)Set the penalty
-bayestopt_.penalty = Inf;
-
-MhDirectoryName = CheckPath('metropolis');
-
-options_.lik_algo = 1;
-OpenOldFile = ones(nblck,1);
-if strcmpi(ProposalFun,'rand_multivariate_normal')
- n = npar;
-elseif strcmpi(ProposalFun,'rand_multivariate_student')
- n = options_.student_degrees_of_freedom;
-end
-% load([MhDirectoryName '/' ModelName '_mh_history.mat'],'record');
-%%%%
-%%%% NOW i run the (nblck-fblck+1) metropolis-hastings chains
-%%%%
-
-
-if any(isnan(bayestopt_.jscale))
- if exist([ModelName '_optimal_mh_scale_parameter.mat'])% This file is created by mode_compute=6.
- load([ModelName '_optimal_mh_scale_parameter'])
- proposal_covariance = d*Scale;
- else
- error('mh:: Something is wrong. I can''t figure out the value of the scale parameter.')
- end
-else
- proposal_covariance = d*diag(bayestopt_.jscale);
-end
-
-
-jloop=0;
-
-for b = fblck:nblck,
- jloop=jloop+1;
- randn('state',record.Seeds(b).Normal);
- rand('state',record.Seeds(b).Unifor);
- if (options_.load_mh_file~=0) & (fline(b)>1) & OpenOldFile(b)
- load(['./' MhDirectoryName '/' ModelName '_mh' int2str(NewFile(b)) ...
- '_blck' int2str(b) '.mat'])
- x2 = [x2;zeros(InitSizeArray(b)-fline(b)+1,npar)];
- logpo2 = [logpo2;zeros(InitSizeArray(b)-fline(b)+1,1)];
- OpenOldFile(b) = 0;
- else
- x2 = zeros(InitSizeArray(b),npar);
- logpo2 = zeros(InitSizeArray(b),1);
- end
- if exist('OCTAVE_VERSION') || options_.console_mode
- diary off
- disp(' ')
- elseif whoiam
- % keyboard;
- waitbarString = ['Please wait... Metropolis-Hastings (' int2str(b) '/' int2str(options_.mh_nblck) ')...'];
- % waitbarTitle=['Metropolis-Hastings ',options_.parallel(ThisMatlab).ComputerName];
- if options_.parallel(ThisMatlab).Local,
- waitbarTitle=['Local '];
- else
- waitbarTitle=[options_.parallel(ThisMatlab).ComputerName];
- end
- fMessageStatus(0,whoiam,waitbarString, waitbarTitle, options_.parallel(ThisMatlab));
- else,
- hh = waitbar(0,['Please wait... Metropolis-Hastings (' int2str(b) '/' int2str(options_.mh_nblck) ')...']);
- set(hh,'Name','Metropolis-Hastings');
-
- end
- isux = 0;
- jsux = 0;
- irun = fline(b);
- j = 1;
- while j <= nruns(b)
- par = feval(ProposalFun, ix2(b,:), proposal_covariance, n);
- if all( par(:) > mh_bounds(:,1) ) & all( par(:) < mh_bounds(:,2) )
- try
- logpost = - feval(TargetFun, par(:),varargin{:});
- catch
- logpost = -inf;
- end
- % testing logposterior DLL
- [junk,logpost1] = logposterior(par(:),varargin{2},mexext);
- if abs(logpost+logpost1) > 1e-10;
- disp ([logpost -logpost1])
- end
- else
- logpost = -inf;
- end
- if (logpost > -inf) && (log(rand) < logpost-ilogpo2(b))
- x2(irun,:) = par;
- ix2(b,:) = par;
- logpo2(irun) = logpost;
- ilogpo2(b) = logpost;
- isux = isux + 1;
- jsux = jsux + 1;
- else
- x2(irun,:) = ix2(b,:);
- logpo2(irun) = ilogpo2(b);
- end
- prtfrc = j/nruns(b);
- if exist('OCTAVE_VERSION') || options_.console_mode
- if mod(j, 10) == 0
- if exist('OCTAVE_VERSION')
- printf('MH: Computing Metropolis-Hastings (chain %d/%d): %3.f%% done, acception rate: %3.f%%\r', b, nblck, 100 * prtfrc, 100 * isux / j);
- else
- fprintf(' MH: Computing Metropolis-Hastings (chain %d/%d): %3.f \b%% done, acceptance rate: %3.f \b%%\r', b, nblck, 100 * prtfrc, 100 * isux / j);
- end
- end
- if mod(j,50)==0 & whoiam
- % keyboard;
- waitbarString = [ '(' int2str(b) '/' int2str(options_.mh_nblck) '), ' sprintf('accept. %3.f%%%%', 100 * isux/j)];
- fMessageStatus(prtfrc,whoiam,waitbarString, '', options_.parallel(ThisMatlab));
- end
- else
- if mod(j, 3)==0 & ~whoiam
- waitbar(prtfrc,hh,[ '(' int2str(b) '/' int2str(options_.mh_nblck) ') ' sprintf('%f done, acceptation rate %f',prtfrc,isux/j)]);
- elseif mod(j,50)==0 & whoiam,
- % keyboard;
- waitbarString = [ '(' int2str(b) '/' int2str(options_.mh_nblck) ') ' sprintf('%f done, acceptation rate %f',prtfrc,isux/j)];
- fMessageStatus(prtfrc,whoiam,waitbarString, waitbarTitle, options_.parallel(ThisMatlab));
- end
- end
-
- if (irun == InitSizeArray(b)) | (j == nruns(b)) % Now I save the simulations
- save([MhDirectoryName '/' ModelName '_mh' int2str(NewFile(b)) '_blck' int2str(b) '.mat'],'x2','logpo2');
- fidlog = fopen([MhDirectoryName '/metropolis.log'],'a');
- fprintf(fidlog,['\n']);
- fprintf(fidlog,['%% Mh' int2str(NewFile(b)) 'Blck' int2str(b) ' (' datestr(now,0) ')\n']);
- fprintf(fidlog,' \n');
- fprintf(fidlog,[' Number of simulations.: ' int2str(length(logpo2)) '\n']);
- fprintf(fidlog,[' Acceptation rate......: ' num2str(jsux/length(logpo2)) '\n']);
- fprintf(fidlog,[' Posterior mean........:\n']);
- for i=1:length(x2(1,:))
- fprintf(fidlog,[' params:' int2str(i) ': ' num2str(mean(x2(:,i))) '\n']);
- end
- fprintf(fidlog,[' log2po:' num2str(mean(logpo2)) '\n']);
- fprintf(fidlog,[' Minimum value.........:\n']);;
- for i=1:length(x2(1,:))
- fprintf(fidlog,[' params:' int2str(i) ': ' num2str(min(x2(:,i))) '\n']);
- end
- fprintf(fidlog,[' log2po:' num2str(min(logpo2)) '\n']);
- fprintf(fidlog,[' Maximum value.........:\n']);
- for i=1:length(x2(1,:))
- fprintf(fidlog,[' params:' int2str(i) ': ' num2str(max(x2(:,i))) '\n']);
- end
- fprintf(fidlog,[' log2po:' num2str(max(logpo2)) '\n']);
- fprintf(fidlog,' \n');
- fclose(fidlog);
- jsux = 0;
- if j == nruns(b) % I record the last draw...
- record.LastParameters(b,:) = x2(end,:);
- record.LastLogLiK(b) = logpo2(end);
- end
- % size of next file in chain b
- InitSizeArray(b) = min(nruns(b)-j,MAX_nruns);
- % initialization of next file if necessary
- if InitSizeArray(b)
- x2 = zeros(InitSizeArray(b),npar);
- logpo2 = zeros(InitSizeArray(b),1);
- NewFile(b) = NewFile(b) + 1;
- irun = 0;
- end
- end
- j=j+1;
- irun = irun + 1;
- end% End of the simulations for one mh-block.
- record.AcceptationRates(b) = isux/j;
- if exist('OCTAVE_VERSION') || options_.console_mode
- if exist('OCTAVE_VERSION')
- printf('\n');
- else
- fprintf('\n');
- end
- diary on;
- elseif ~whoiam
- close(hh);
- end
- record.Seeds(b).Normal = randn('state');
- record.Seeds(b).Unifor = rand('state');
- OutputFileName(jloop,:) = {[MhDirectoryName,filesep], [ModelName '_mh*_blck' int2str(b) '.mat']};
-end% End of the loop over the mh-blocks.
-
-
-myoutput.record = record;
-myoutput.irun = irun;
-myoutput.NewFile = NewFile;
-myoutput.OutputFileName = OutputFileName;
\ No newline at end of file
diff --git a/mex/sources/estimation/tests/logposterior_dll_test/rawdata_euromodel_1.m b/mex/sources/estimation/tests/logposterior_dll_test/rawdata_euromodel_1.m
deleted file mode 100644
index 25bbc92414efddc7adf66d5ab4cc8545af1e71f7..0000000000000000000000000000000000000000
--- a/mex/sources/estimation/tests/logposterior_dll_test/rawdata_euromodel_1.m
+++ /dev/null
@@ -1,967 +0,0 @@
-C =[
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- -6.1860
- -6.5983
- -5.6088
- -5.0547
- -4.4774
- -3.8081
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- 2.5435
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- 3.2007
- 2.6705
- 3.0518
- 3.2445
- 3.8443
- 3.8525
- 4.9494
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- 4.9532
- 5.1441
- 3.7124
- 3.9880
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- 2.6005
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- 0.2104
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- 0.3555
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- 1.3269
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- 1.4308
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- 1.9842
- 2.3948
- 2.8710
- 3.0177
- 2.9305
- 3.1739
- 3.7380
- 3.8285
- 3.3342
- 3.7447
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- 3.1039
- 2.8413
- 3.0338
- 0.3669
- 0.0847
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- -2.3320
- -2.2768
- -2.1816
- -2.1043
- -1.8969
- -2.2388
- -2.1679
- -2.1172
-];
-
-E =[
- 0.6263
- 0.7368
- 0.7477
- 1.0150
- 0.6934
- 0.4135
- 0.3845
- 0.2380
- 0.2853
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- 1.0323
- 1.3420
- 1.6902
- 2.0680
- 2.8219
- 3.2511
- 3.2930
- 3.5633
- 3.8992
- 3.6874
- 3.2849
- 3.1614
- 2.6221
- 2.5067
- 1.9223
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- 0.4483
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- 1.5431
-];
-
-I =[
- 2.6617
- 2.4325
- 1.9592
- 3.2530
- 2.9949
- 3.7918
- 4.7444
- 4.8289
- 5.5983
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- -2.8472
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- 4.0327
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- 7.1400
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- 8.5609
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- 3.2780
- 3.5985
- 4.9011
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- 6.4402
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-
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-R =[
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- -0.3791
- -0.4020
- -0.4166
- -0.4037
- -0.3636
- -0.4075
- -0.4311
- -0.4470
- -0.5111
- -0.6274
- -0.7261
- -0.6974
- -0.5012
-];
-
-W =[
- -14.8791
- -13.2300
- -13.5037
- -13.0249
- -11.2546
- -10.0148
- -8.8586
- -8.5739
- -7.7851
- -6.7136
- -5.5878
- -4.6881
- -3.8039
- -3.0366
- -2.7342
- -1.3135
- -0.7387
- -0.1131
- -0.2769
- 0.8696
- 1.8855
- 2.3667
- 2.4942
- 3.2049
- 3.9682
- 5.1500
- 4.7047
- 4.7827
- 5.3377
- 5.6614
- 5.2813
- 5.2967
- 5.5175
- 6.1526
- 5.6627
- 6.0694
- 6.5824
- 6.9032
- 6.7849
- 6.6896
- 6.6201
- 6.9933
- 5.8959
- 6.7419
- 6.9999
- 6.4009
- 5.5083
- 5.1054
- 5.2813
- 4.5790
- 3.9589
- 3.8599
- 3.8978
- 2.7957
- 3.2480
- 1.4634
- 1.9219
- 1.8398
- 1.9279
- 1.8316
- 1.6092
- 1.2741
- 0.2031
- -0.0236
- -0.1004
- -0.3034
- -1.0273
- -0.2205
- 0.0458
- 0.2386
- -0.0977
- -0.3145
- -0.1416
- -0.7009
- -0.9082
- -0.8802
- -0.5644
- -0.5852
- -0.5346
- 0.0652
- 0.1301
- 0.3444
- -0.3592
- 0.8096
- 0.9644
- 1.0289
- 1.2781
- 1.2298
- 2.2134
- 2.0808
- 0.4925
- 0.6506
- 0.5531
- 0.2456
- -0.5351
- -0.8183
- -0.8967
- -0.7268
- -1.0738
- -1.2844
- -1.4338
- -1.6995
- -1.7085
- -2.2889
- -2.1018
- -2.4273
- -2.4609
- -2.1407
- -2.3847
- -3.1689
- -4.5581
- -4.1027
- -4.2436
- -4.8836
- -5.9660
- -4.9971
- -5.2386
- -5.6618
-];
-
-Y =[
- -4.9347
- -4.6205
- -5.2198
- -4.5937
- -3.8015
- -3.6643
- -2.7239
- -2.7524
- -2.0634
- -1.0112
- 0.0530
- 0.7623
- 1.7927
- 2.1486
- 2.4866
- 2.1456
- 2.1671
- -0.0254
- -1.6716
- -1.9673
- -1.6109
- -1.0292
- -0.1222
- 0.7329
- 1.1234
- 2.0603
- 1.7998
- 1.4820
- 1.1732
- 1.6424
- 1.5382
- 2.1399
- 2.0127
- 2.7210
- 2.4966
- 3.5249
- 3.6237
- 4.2011
- 4.5634
- 3.3442
- 2.7761
- 1.9812
- 1.3779
- 1.4616
- 1.3029
- 0.7594
- 0.3695
- 0.0832
- -0.8118
- -1.4557
- -1.4850
- -1.2346
- -1.5696
- -1.3785
- -0.7682
- -2.0308
- -1.7778
- -1.7801
- -2.1711
- -1.7469
- -1.3413
- -1.3352
- -2.4390
- -1.2125
- -1.1695
- -1.0891
- -2.4753
- -1.3503
- -0.9412
- -0.1470
- 0.0026
- 0.1108
- 0.6890
- 1.3520
- 1.6018
- 2.0667
- 1.7625
- 2.6658
- 3.4048
- 3.2507
- 3.4251
- 3.2174
- 3.1903
- 3.3396
- 3.1358
- 2.8625
- 3.3546
- 2.4609
- 1.9534
- 0.9962
- -0.7904
- -1.1672
- -1.2586
- -1.3593
- -1.3443
- -0.9413
- -0.6023
- -0.4516
- -0.5129
- -0.8741
- -1.0784
- -1.4091
- -1.3627
- -1.5731
- -1.6037
- -1.8814
- -2.1482
- -1.3597
- -1.1855
- -1.1122
- -0.8424
- -0.9747
- -1.1385
- -1.4548
- -1.4284
- -1.4633
- -1.0621
- -0.7871
-];
diff --git a/mex/sources/estimation/tests/logposterior_dll_test/sweuromodel_dll.mod b/mex/sources/estimation/tests/logposterior_dll_test/sweuromodel_dll.mod
deleted file mode 100644
index a6a19f55b1dde641b63922f58cfee92edee233f1..0000000000000000000000000000000000000000
--- a/mex/sources/estimation/tests/logposterior_dll_test/sweuromodel_dll.mod
+++ /dev/null
@@ -1,184 +0,0 @@
-//options_.usePartInfo=1;
-
-var MC E EF R_KF QF CF IF YF LF PIEF WF RF R_K Q C I Y L PIE W R EE_A PIE_BAR EE_B EE_G EE_L EE_I KF K one BIGTHETA;
-
-varexo E_A E_B E_G E_L E_I ETA_R E_PIE_BAR ETA_Q ETA_P ETA_W ;
-
-parameters
-xi_e lambda_w alpha czcap beta phi_i tau sig_c hab ccs cinvs phi_y gamma_w xi_w gamma_p xi_p sig_l r_dpi
-r_pie r_dy r_y rho rho_a rho_pb rho_b rho_g rho_l rho_i LMP ;
-
-
-
-alpha=.30;
-beta=.99;
-tau=0.025;
-ccs=0.6;
-cinvs=.22; //% alpha*(tau+ctrend)/R_K R_K=ctrend/beta-1+tau
-lambda_w = 0.5;
-phi_i= 6.771;
-sig_c= 1.353;
-hab= 0.573;
-xi_w= 0.737;
-sig_l= 2.400;
-xi_p= 0.908;
-xi_e= 0.599;
-gamma_w= 0.763;
-gamma_p= 0.469;
-czcap= 0.169;
-phi_y= 1.408;
-r_pie= 1.684;
-r_dpi= 0.14;
-rho= 0.961;
-r_y= 0.099;
-r_dy= 0.159;
-rho_a= 0.823;
-rho_b= 0.855;
-rho_g= 0.949;
-rho_l= 0.889;
-rho_i= 0.927;
-rho_pb= 0.924;
-LMP = 0.0 ; //NEW.
-
-model(linear, use_dll);
- CF = (1/(1+hab))*(CF(1)+hab*CF(-1))-((1-hab)/((1+hab)*sig_c))*(RF-PIEF(1)-EE_B) ;
- 0 = alpha*R_KF+(1-alpha)*WF -EE_A ;
- PIEF = 0*one;
- IF = (1/(1+beta))* (( IF(-1) + beta*(IF(1)))+(1/phi_i)*QF)+0*ETA_Q+EE_I ;
- QF = -(RF-PIEF(1))+(1-beta*(1-tau))*((0+czcap)/czcap)*R_KF(1)+beta*(1-tau)*QF(1) +0*EE_I ;
- KF = (1-tau)*KF(-1)+tau*IF(-1) ;
- YF = (ccs*CF+cinvs*IF)+EE_G ;
-
- YF = 1*phi_y*( alpha*KF+alpha*(1/czcap)*R_KF+(1-alpha)*LF+EE_A ) ;
- WF = (sig_c/(1-hab))*(CF-hab*CF(-1)) + sig_l*LF - EE_L ;
- LF = R_KF*((1+czcap)/czcap)-WF+KF ;
- EF = EF(-1)+EF(1)-EF+(LF-EF)*((1-xi_e)*(1-xi_e*beta)/(xi_e));
-
- C = (hab/(1+hab))*C(-1)+(1/(1+hab))*C(1)-((1-hab)/((1+hab)*sig_c))*(R-PIE(1)-EE_B) ;
- I = (1/(1+beta))* (( I(-1) + beta*(I(1)))+(1/phi_i)*Q )+1*ETA_Q+1*EE_I ;
- Q = -(R-PIE(1))+(1-beta*(1-tau))*((0+czcap)/czcap)*R_K(1)+beta*(1-tau)*Q(1) +EE_I*0+0*ETA_Q ;
- K = (1-tau)*K(-1)+tau*I(-1) ;
- Y = (ccs*C+cinvs*I)+ EE_G ;
- Y = phi_y*( alpha*K+alpha*(1/czcap)*R_K+(1-alpha)*L ) +phi_y*EE_A ;
- PIE = (1/(1+beta*gamma_p))*
- (
- (beta)*(PIE(1)) +(gamma_p)*(PIE(-1))
- +((1-xi_p)*(1-beta*xi_p)/(xi_p))*(MC)
- ) + ETA_P ;
-
- MC = alpha*R_K+(1-alpha)*W -EE_A;
- W = (1/(1+beta))*(beta*W(+1)+W(-1))
- +(beta/(1+beta))*(PIE(+1))
- -((1+beta*gamma_w)/(1+beta))*(PIE)
- +(gamma_w/(1+beta))*(PIE(-1))
- -(1/(1+beta))*(((1-beta*xi_w)*(1-xi_w))/(((1+(((1+lambda_w)*sig_l)/(lambda_w))))*xi_w))*(W-sig_l*L-(sig_c/(1-hab))*(C-hab*C(-1))+EE_L)
- +ETA_W;
- L = R_K*((1+czcap)/czcap)-W+K ;
-
-// R = r_dpi*(PIE-PIE(-1))
-// +(1-rho)*(r_pie*(PIE(-1)-PIE_BAR)+r_y*(Y-YF))
-// +r_dy*(Y-YF-(Y(-1)-YF(-1)))
-// +rho*(R(-1)-PIE_BAR)
-// +PIE_BAR
-// +ETA_R;
-
-
- R =
-
-r_dpi*(PIE-PIE(-1))
-
- +(1-rho)*(r_pie*(BIGTHETA)+r_y*(Y-YF))
- +r_dy*(Y-YF-(Y(-1)-YF(-1)))
- +rho*(R(-1)-PIE_BAR)
- +PIE_BAR
- +ETA_R;
-
-
- E = E(-1)+E(1)-E+(L-E)*((1-xi_e)*(1-xi_e*beta)/(xi_e));
-
-
- EE_A = (rho_a)*EE_A(-1) + E_A;
- PIE_BAR = rho_pb*PIE_BAR(-1)+ E_PIE_BAR ;
- EE_B = rho_b*EE_B(-1) + E_B ;
- EE_G = rho_g*EE_G(-1) + E_G ;
- EE_L = rho_l*EE_L(-1) + E_L ;
- EE_I = rho_i*EE_I(-1) + E_I ;
- one = 0*one(-1) ;
-
- LMP*BIGTHETA(1) = BIGTHETA - (PIE(-1) - PIE_BAR) ;
-
-end;
-
-
-shocks;
-var E_A; stderr 0.598;
-var E_B; stderr 0.336;
-var E_G; stderr 0.325;
-var E_I; stderr 0.085;
-var E_L; stderr 3.520;
-var ETA_P; stderr 0.160;
-var ETA_W; stderr 0.289;
-var ETA_R; stderr 0.081;
-var ETA_Q; stderr 0.604;
-var E_PIE_BAR; stderr 0.017;
-end;
-
-//stoch_simul(irf=20) Y C PIE R W R_K L Q I K ;
-
-// stoch_simul generates what kind of standard errors for the shocks ?
-
-//steady;
-//check;
-//stoch_simul(periods=200,irf=20,simul_seed=3) Y C PIE MC R W R_K E L I ;
-
-//datatomfile('ddd',[]);
-
-// new syntax
-
-estimated_params;
-// PARAM NAME, INITVAL, LB, UB, PRIOR_SHAPE, PRIOR_P1, PRIOR_P2, PRIOR_P3, PRIOR_P4, JSCALE
-// PRIOR_SHAPE: BETA_PDF, GAMMA_PDF, NORMAL_PDF, INV_GAMMA_PDF
-stderr E_A,0.543,0.01,4,INV_GAMMA_PDF,0.4,2;
-stderr E_PIE_BAR,0.072,0.001,4,INV_GAMMA_PDF,0.02,10;
-stderr E_B,0.2694,0.01,4,INV_GAMMA_PDF,0.2,2;
-stderr E_G,0.3052,0.01,4,INV_GAMMA_PDF,0.3,2;
-stderr E_L,1.4575,0.1,6,INV_GAMMA_PDF,1,2;
-stderr E_I,0.1318,0.01,4,INV_GAMMA_PDF,0.1,2;
-stderr ETA_R,0.1363,0.01,4,INV_GAMMA_PDF,0.1,2;
-stderr ETA_Q,0.4842,0.01,4,INV_GAMMA_PDF,0.4,2;
-stderr ETA_P,0.1731,0.01,4,INV_GAMMA_PDF,0.15,2;
-stderr ETA_W,0.2462,0.1,4,INV_GAMMA_PDF,0.25,2;
-rho_a,.9722,.1,.9999,BETA_PDF,0.85,0.1;
-rho_pb,.85,.1,.999,BETA_PDF,0.85,0.1;
-rho_b,.7647,.1,.99,BETA_PDF,0.85,0.1;
-rho_g,.9502,.1,.9999,BETA_PDF,0.85,0.1;
-rho_l,.9542,.1,.9999,BETA_PDF,0.85,0.1;
-rho_i,.6705,.1,.99,BETA_PDF,0.85,0.1;
-phi_i,5.2083,1,15,NORMAL_PDF,4,1.5;
-sig_c,0.9817,0.25,3,NORMAL_PDF,1,0.375;
-hab,0.5612,0.3,0.95,BETA_PDF,0.7,0.1;
-xi_w,0.7661,0.3,0.9,BETA_PDF,0.75,0.05;
-sig_l,1.7526,0.5,5,NORMAL_PDF,2,0.75;
-xi_p,0.8684,0.3,0.95,BETA_PDF,0.75,0.05;
-xi_e,0.5724,0.1,0.95,BETA_PDF,0.5,0.15;
-gamma_w,0.6202,0.1,0.99,BETA_PDF,0.75,0.15;
-gamma_p,0.6638,0.1,0.99,BETA_PDF,0.75,0.15;
-czcap,0.2516,0.01,2,NORMAL_PDF,0.2,0.075;
-phi_y,1.3011,1.001,2,NORMAL_PDF,1.45,0.125;
-r_pie,1.4616,1.2,2,NORMAL_PDF,1.7,0.1;
-r_dpi,0.1144,0.01,0.5,NORMAL_PDF,0.3,0.1;
-rho,0.8865,0.5,0.99,BETA_PDF,0.8,0.10;
-r_y,0.0571,0.01,0.2,NORMAL_PDF,0.125,0.05;
-r_dy,0.2228,0.05,0.5,NORMAL_PDF,0.0625,0.05;
-end;
-
-varobs Y C I E PIE W R;
-
-//estimation(datafile=rawdata_euromodel_1,presample=40, first_obs=1, nobs=118, lik_init=2, mode_compute=1,mh_replic=0);
-estimation(datafile=rawdata_euromodel_1,presample=40, first_obs=1, nobs=118,mh_jscale=0.2,mh_replic=1000
-//,mode_compute=0,mode_file=sweuromodel_dll_mode
-);
-
-
-//stoch_simul(periods=200,irf=20,simul_seed=3) Y C PIE R W R_K L Q I K ;
-
diff --git a/mex/sources/estimation/tests/random_walk_metropolis_hastings_core.m b/mex/sources/estimation/tests/random_walk_metropolis_hastings_core.m
deleted file mode 100644
index 14646c1578d231f9ed7d05356e3a11ab1988fcf6..0000000000000000000000000000000000000000
--- a/mex/sources/estimation/tests/random_walk_metropolis_hastings_core.m
+++ /dev/null
@@ -1,309 +0,0 @@
-function myoutput = random_walk_metropolis_hastings_core(myinputs,fblck,nblck,whoiam, ThisMatlab)
-% PARALLEL CONTEXT
-% This function contain the most computationally intensive portion of code in
-% random_walk_metropolis_hastings (the 'for xxx = fblck:nblck' loop). The branches in 'for'
-% cycle and are completely independent than suitable to be executed in parallel way.
-%
-% INPUTS
-% o myimput [struc] The mandatory variables for local/remote
-% parallel computing obtained from random_walk_metropolis_hastings.m
-% function.
-% o fblck and nblck [integer] The Metropolis-Hastings chains.
-% o whoiam [integer] In concurrent programming a modality to refer to the differents thread running in parallel is needed.
-% The integer whoaim is the integer that
-% allows us to distinguish between them. Then it is the index number of this CPU among all CPUs in the
-% cluster.
-% o ThisMatlab [integer] Allows us to distinguish between the
-% 'main' matlab, the slave matlab worker, local matlab, remote matlab,
-% ... Then it is the index number of this slave machine in the cluster.
-% OUTPUTS
-% o myoutput [struc]
-% If executed without parallel is the original output of 'for b =
-% fblck:nblck' otherwise a portion of it computed on a specific core or
-% remote machine. In this case:
-% record;
-% irun;
-% NewFile;
-% OutputFileName
-%
-% ALGORITHM
-% Portion of Metropolis-Hastings.
-%
-% SPECIAL REQUIREMENTS.
-% None.
-
-% PARALLEL CONTEXT
-% The most computationally intensive part of this function may be executed
-% in parallel. The code sutable to be executed in parallel on multi core or cluster machine,
-% is removed from this function and placed in random_walk_metropolis_hastings_core.m funtion.
-% Then the DYNARE parallel package contain a set of pairs matlab functios that can be executed in
-% parallel and called name_function.m and name_function_core.m.
-% In addition in the parallel package we have second set of functions used
-% to manage the parallel computation.
-%
-% This function was the first function to be parallelized, later other
-% functions have been parallelized using the same methodology.
-% Then the comments write here can be used for all the other pairs of
-% parallel functions and also for management funtions.
-
-
-% Copyright (C) 2006-2010 Dynare Team
-%
-% This file is part of Dynare.
-%
-% Dynare is free software: you can redistribute it and/or modify
-% it under the terms of the GNU General Public License as published by
-% the Free Software Foundation, either version 3 of the License, or
-% (at your option) any later version.
-%
-% Dynare is distributed in the hope that it will be useful,
-% but WITHOUT ANY WARRANTY; without even the implied warranty of
-% MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
-% GNU General Public License for more details.
-%
-% You should have received a copy of the GNU General Public License
-% along with Dynare. If not, see <http://www.gnu.org/licenses/>.
-
-if nargin<4,
- whoiam=0;
-end
-
-
-global bayestopt_ estim_params_ options_ M_ oo_
-
-% reshape 'myinputs' for local computation.
-% In order to avoid confusion in the name space, the instruction struct2local(myinputs) is replaced by:
-
-TargetFun=myinputs.TargetFun;
-ProposalFun=myinputs.ProposalFun;
-xparam1=myinputs.xparam1;
-vv=myinputs.vv;
-mh_bounds=myinputs.mh_bounds;
-ix2=myinputs.ix2;
-ilogpo2=myinputs.ilogpo2;
-ModelName=myinputs.ModelName;
-fline=myinputs.fline;
-npar=myinputs.npar;
-nruns=myinputs.nruns;
-NewFile=myinputs.NewFile;
-MAX_nruns=myinputs.MAX_nruns;
-d=myinputs.d;
-InitSizeArray=myinputs.InitSizeArray;
-record=myinputs.record;
-varargin=myinputs.varargin;
-
-% Necessary only for remote computing!
-if whoiam
- Parallel=myinputs.Parallel;
- MasterName=myinputs.MasterName;
- DyMo=myinputs.DyMo;
- % initialize persistent variables in priordens()
- priordens(xparam1,bayestopt_.pshape,bayestopt_.p6,bayestopt_.p7, ...
- bayestopt_.p3,bayestopt_.p4,1);
-end
-
-% (re)Set the penalty
-bayestopt_.penalty = Inf;
-
-MhDirectoryName = CheckPath('metropolis');
-
-options_.lik_algo = 1;
-OpenOldFile = ones(nblck,1);
-if strcmpi(ProposalFun,'rand_multivariate_normal')
- n = npar;
-elseif strcmpi(ProposalFun,'rand_multivariate_student')
- n = options_.student_degrees_of_freedom;
-end
-% load([MhDirectoryName '/' ModelName '_mh_history.mat'],'record');
-%%%%
-%%%% NOW i run the (nblck-fblck+1) metropolis-hastings chains
-%%%%
-jscale = diag(bayestopt_.jscale);
-
-jloop=0;
-if options_.use_dll==1
-
-%%%TEST%%%
-oldoptions_console_mode=options_.console_mode;
-%options_.console_mode=1;
-
- if exist('OCTAVE_VERSION')
- oldoptions_console_mode=options_.console_mode;
- options_.console_mode=1;
- end
- for b = fblck:nblck,
- record.Seeds(b).Normal = randn('state');
- record.Seeds(b).Unifor = rand('state');
- end
- % calculate draws and get last line run in the last MH block sub-array
- [err irun] = logMHMCMCposterior( xparam1, varargin{2}, mexext, fblck, nblck, nruns, vv)
- mexErrCheck('logMHMCMCposterior',err);
- if irun<0
- error('Error in logMHMCMCposterior');
- end
- for b = fblck:nblck,
- record.Seeds(b).Normal = randn('state');
- record.Seeds(b).Unifor = rand('state');
- OutputFileName(b,:) = {[MhDirectoryName,filesep], [ModelName '_mh*_blck' int2str(b) '.mat']};
- end
-
- if exist('OCTAVE_VERSION')
- options_.console_mode=oldoptions_console_mode;
- options_.console_mode=1;
- end
- record.AcceptationRates=record_AcceptationRates;
- record.LastLogLiK=record_LastLogLiK;
- record.LastParameters=record_LastParameters;
- options_.console_mode=oldoptions_console_mode;
-else
- for b = fblck:nblck,
- jloop=jloop+1;
- randn('state',record.Seeds(b).Normal);
- rand('state',record.Seeds(b).Unifor);
- if (options_.load_mh_file~=0) & (fline(b)>1) & OpenOldFile(b)
- load(['./' MhDirectoryName '/' ModelName '_mh' int2str(NewFile(b)) ...
- '_blck' int2str(b) '.mat'])
- x2 = [x2;zeros(InitSizeArray(b)-fline(b)+1,npar)];
- logpo2 = [logpo2;zeros(InitSizeArray(b)-fline(b)+1,1)];
- OpenOldFile(b) = 0;
- else
- x2 = zeros(InitSizeArray(b),npar);
- logpo2 = zeros(InitSizeArray(b),1);
- end
- if exist('OCTAVE_VERSION') || options_.console_mode
- diary off
- disp(' ')
- elseif whoiam
- % keyboard;
- waitbarString = ['Please wait... Metropolis-Hastings (' int2str(b) '/' int2str(options_.mh_nblck) ')...'];
- % waitbarTitle=['Metropolis-Hastings ',options_.parallel(ThisMatlab).PcName];
- if options_.parallel(ThisMatlab).Local,
- waitbarTitle=['Local '];
- else
- waitbarTitle=[options_.parallel(ThisMatlab).PcName];
- end
- fMessageStatus(0,whoiam,waitbarString, waitbarTitle, options_.parallel(ThisMatlab), MasterName, DyMo);
- else,
- hh = waitbar(0,['Please wait... Metropolis-Hastings (' int2str(b) '/' int2str(options_.mh_nblck) ')...']);
- set(hh,'Name','Metropolis-Hastings');
-
- end
- isux = 0;
- jsux = 0;
- irun = fline(b);
- j = 1;
- load urand_1_1.csv
- load paramdraws_1_1.csv
- while j <= nruns(b)
- par = feval(ProposalFun, ix2(b,:), d * jscale, n);
- par=paramdraws_1_1(j,:);
- if all( par(:) > mh_bounds(:,1) ) & all( par(:) < mh_bounds(:,2) )
- try
- logpost = - feval(TargetFun, par(:),varargin{:});
- catch
- logpost = -inf;
- end
- else
- logpost = -inf;
- end
- lurand=log(urand_1_1(j));
-% if (logpost > -inf) && (log(rand) < logpost-ilogpo2(b))
- if (logpost > -inf) && (lurand < logpost-ilogpo2(b))
- x2(irun,:) = par;
- ix2(b,:) = par;
- logpo2(irun) = logpost;
- ilogpo2(b) = logpost;
- isux = isux + 1;
- jsux = jsux + 1;
- else
- x2(irun,:) = ix2(b,:);
- logpo2(irun) = ilogpo2(b);
- end
- prtfrc = j/nruns(b);
- if exist('OCTAVE_VERSION') || options_.console_mode
- if mod(j, 10) == 0
- if exist('OCTAVE_VERSION')
- printf('MH: Computing Metropolis-Hastings (chain %d/%d): %3.f%% done, acception rate: %3.f%%\r', b, nblck, 100 * prtfrc, 100 * isux / j);
- else
- fprintf(' MH: Computing Metropolis-Hastings (chain %d/%d): %3.f \b%% done, acceptance rate: %3.f \b%%\r', b, nblck, 100 * prtfrc, 100 * isux / j);
- end
- end
- if mod(j,50)==0 & whoiam
- % keyboard;
- waitbarString = [ '(' int2str(b) '/' int2str(options_.mh_nblck) '), ' sprintf('accept. %3.f%%%%', 100 * isux/j)];
- fMessageStatus(prtfrc,whoiam,waitbarString, '', options_.parallel(ThisMatlab), MasterName, DyMo)
- end
- else
- if mod(j, 3)==0 & ~whoiam
- waitbar(prtfrc,hh,[ '(' int2str(b) '/' int2str(options_.mh_nblck) ') ' sprintf('%f done, acceptation rate %f',prtfrc,isux/j)]);
- elseif mod(j,50)==0 & whoiam,
- % keyboard;
- waitbarString = [ '(' int2str(b) '/' int2str(options_.mh_nblck) ') ' sprintf('%f done, acceptation rate %f',prtfrc,isux/j)];
- fMessageStatus(prtfrc,whoiam,waitbarString, waitbarTitle, options_.parallel(ThisMatlab), MasterName, DyMo)
- end
- end
-
- if (irun == InitSizeArray(b)) | (j == nruns(b)) % Now I save the simulations
- save([MhDirectoryName '/' ModelName '_mh' int2str(NewFile(b)) '_blck' int2str(b) '.mat'],'x2','logpo2');
- fidlog = fopen([MhDirectoryName '/metropolis.log'],'a');
- fprintf(fidlog,['\n']);
- fprintf(fidlog,['%% Mh' int2str(NewFile(b)) 'Blck' int2str(b) ' (' datestr(now,0) ')\n']);
- fprintf(fidlog,' \n');
- fprintf(fidlog,[' Number of simulations.: ' int2str(length(logpo2)) '\n']);
- fprintf(fidlog,[' Acceptation rate......: ' num2str(jsux/length(logpo2)) '\n']);
- fprintf(fidlog,[' Posterior mean........:\n']);
- for i=1:length(x2(1,:))
- fprintf(fidlog,[' params:' int2str(i) ': ' num2str(mean(x2(:,i))) '\n']);
- end
- fprintf(fidlog,[' log2po:' num2str(mean(logpo2)) '\n']);
- fprintf(fidlog,[' Minimum value.........:\n']);;
- for i=1:length(x2(1,:))
- fprintf(fidlog,[' params:' int2str(i) ': ' num2str(min(x2(:,i))) '\n']);
- end
- fprintf(fidlog,[' log2po:' num2str(min(logpo2)) '\n']);
- fprintf(fidlog,[' Maximum value.........:\n']);
- for i=1:length(x2(1,:))
- fprintf(fidlog,[' params:' int2str(i) ': ' num2str(max(x2(:,i))) '\n']);
- end
- fprintf(fidlog,[' log2po:' num2str(max(logpo2)) '\n']);
- fprintf(fidlog,' \n');
- fclose(fidlog);
- jsux = 0;
- if j == nruns(b) % I record the last draw...
- record.LastParameters(b,:) = x2(end,:);
- record.LastLogLiK(b) = logpo2(end);
- end
- % size of next file in chain b
- InitSizeArray(b) = min(nruns(b)-j,MAX_nruns);
- % initialization of next file if necessary
- if InitSizeArray(b)
- x2 = zeros(InitSizeArray(b),npar);
- logpo2 = zeros(InitSizeArray(b),1);
- NewFile(b) = NewFile(b) + 1;
- irun = 0;
- end
- end
- j=j+1;
- irun = irun + 1;
- end% End of the simulations for one mh-block.
- record.AcceptationRates(b) = isux/j;
- if exist('OCTAVE_VERSION') || options_.console_mode
- if exist('OCTAVE_VERSION')
- printf('\n');
- else
- fprintf('\n');
- end
- diary on;
- elseif ~whoiam
- close(hh);
- end
- record.Seeds(b).Normal = randn('state');
- record.Seeds(b).Unifor = rand('state');
- OutputFileName(jloop,:) = {[MhDirectoryName,filesep], [ModelName '_mh*_blck' int2str(b) '.mat']};
- end% End of the loop over the mh-blocks.
-end % if use_dll
-
-myoutput.record = record;
-myoutput.irun = irun;
-myoutput.NewFile = NewFile;
-myoutput.OutputFileName = OutputFileName;
diff --git a/mex/sources/estimation/tests/rawdata_euromodel_1.m b/mex/sources/estimation/tests/rawdata_euromodel_1.m
deleted file mode 100644
index 25bbc92414efddc7adf66d5ab4cc8545af1e71f7..0000000000000000000000000000000000000000
--- a/mex/sources/estimation/tests/rawdata_euromodel_1.m
+++ /dev/null
@@ -1,967 +0,0 @@
-C =[
- -7.4073
- -6.1860
- -6.5983
- -5.6088
- -5.0547
- -4.4774
- -3.8081
- -3.8425
- -2.4178
- -1.9835
- -1.0395
- -0.1583
- -0.0397
- 0.3505
- -0.1879
- -0.0067
- 0.0478
- -1.2247
- -1.4349
- -0.7973
- -0.0461
- 0.5844
- 1.1372
- 1.3801
- 1.8023
- 2.2972
- 2.0469
- 2.5435
- 2.8169
- 3.2007
- 2.6705
- 3.0518
- 3.2445
- 3.8443
- 3.8525
- 4.9494
- 4.2770
- 4.9532
- 5.1441
- 3.7124
- 3.9880
- 3.6926
- 2.6005
- 1.8679
- 1.9085
- 1.5563
- 1.2308
- 0.3264
- -0.2208
- -0.2483
- -0.4082
- -1.0315
- -1.6030
- -1.5499
- -1.3777
- -2.1675
- -2.5138
- -2.8820
- -2.6958
- -2.4719
- -1.9854
- -1.7954
- -2.2362
- -1.0595
- -0.8808
- -0.8548
- -1.2839
- -0.1363
- 0.2104
- 0.8810
- 0.3555
- 0.4766
- 1.3269
- 1.4506
- 1.4308
- 1.6263
- 1.9842
- 2.3948
- 2.8710
- 3.0177
- 2.9305
- 3.1739
- 3.7380
- 3.8285
- 3.3342
- 3.7447
- 3.7830
- 3.1039
- 2.8413
- 3.0338
- 0.3669
- 0.0847
- 0.0104
- 0.2115
- -0.6649
- -0.9625
- -0.7330
- -0.8664
- -1.4441
- -1.0179
- -1.2729
- -1.9539
- -1.4427
- -2.0371
- -1.9764
- -2.5654
- -2.8570
- -2.5842
- -3.0427
- -2.8312
- -2.3320
- -2.2768
- -2.1816
- -2.1043
- -1.8969
- -2.2388
- -2.1679
- -2.1172
-];
-
-E =[
- 0.6263
- 0.7368
- 0.7477
- 1.0150
- 0.6934
- 0.4135
- 0.3845
- 0.2380
- 0.2853
- 0.5999
- 0.8622
- 1.2116
- 1.4921
- 1.5816
- 1.7259
- 1.6276
- 1.2422
- 0.8084
- 0.4710
- -0.3704
- -0.6427
- -0.5323
- -0.5562
- -0.3651
- -0.4356
- -0.7164
- -0.5816
- -0.4635
- -0.8456
- -0.9708
- -0.7138
- -0.7499
- -0.6941
- -0.6656
- -0.2912
- -0.1650
- 0.0774
- 0.2307
- 0.4484
- 0.4942
- 0.4653
- 0.2196
- 0.1736
- -0.1595
- -0.3918
- -0.4611
- -0.8493
- -0.7384
- -1.0604
- -1.2166
- -1.7187
- -1.6932
- -1.7830
- -1.7035
- -2.2079
- -2.3769
- -2.2511
- -2.1093
- -2.4638
- -2.4027
- -2.1313
- -1.9199
- -1.7941
- -1.4661
- -1.2269
- -1.0392
- -1.0725
- -0.7156
- -0.4778
- -0.4233
- -0.0409
- 0.1620
- 0.4280
- 0.5873
- 1.0323
- 1.3420
- 1.6902
- 2.0680
- 2.8219
- 3.2511
- 3.2930
- 3.5633
- 3.8992
- 3.6874
- 3.2849
- 3.1614
- 2.6221
- 2.5067
- 1.9223
- 1.1777
- 0.4483
- -0.0661
- -0.4424
- -0.9000
- -1.1478
- -1.2047
- -1.1412
- -1.2383
- -1.1048
- -0.9716
- -0.9287
- -1.0057
- -1.0827
- -1.0200
- -1.0072
- -1.1740
- -1.2809
- -1.1086
- -0.9866
- -0.8947
- -0.5875
- -0.2329
- 0.1493
- 0.4906
- 0.8400
- 1.0720
- 1.2648
- 1.5431
-];
-
-I =[
- 2.6617
- 2.4325
- 1.9592
- 3.2530
- 2.9949
- 3.7918
- 4.7444
- 4.8289
- 5.5983
- 7.8923
- 9.4297
- 9.5010
- 10.0150
- 10.0413
- 9.6046
- 6.4766
- 5.9647
- 3.0114
- 0.5683
- -2.1226
- -2.1855
- -0.8329
- -1.5207
- -1.3419
- -1.7897
- -0.1476
- 0.4675
- -1.6516
- -1.5419
- -1.3050
- -1.2451
- -0.7815
- -0.7796
- -0.3612
- -2.4072
- 1.1162
- 1.1383
- 3.4132
- 5.0356
- 2.8016
- 2.1734
- 0.9366
- -0.7050
- -1.5021
- -2.9868
- -6.0237
- -6.2589
- -6.9138
- -8.2340
- -9.2589
- -9.2465
- -9.6988
- -9.7782
- -10.5645
- -10.7544
- -13.1583
- -12.2718
- -12.0131
- -13.5983
- -12.3579
- -10.9146
- -11.1572
- -12.4935
- -9.4393
- -8.5535
- -7.3723
- -10.0169
- -6.6088
- -5.2045
- -4.1024
- -2.8472
- -1.3139
- 0.0477
- 1.5629
- 3.6947
- 4.0327
- 4.1320
- 7.1400
- 9.1036
- 8.5609
- 7.6576
- 8.8022
- 8.9611
- 10.0871
- 9.4797
- 9.3964
- 10.0363
- 8.6340
- 6.6522
- 4.4471
- 0.2854
- -2.1879
- -2.9879
- -4.1021
- -2.7713
- -2.2281
- -1.2908
- -0.3250
- 0.6534
- 0.3942
- 0.3534
- -0.1532
- -1.7936
- 0.4909
- 0.3634
- 0.4290
- -0.9709
- 0.1942
- 0.6103
- 1.4426
- 2.7225
- 1.7525
- 3.2780
- 3.5985
- 4.9011
- 5.3312
- 6.4402
- 6.6529
-];
-
-L =[
- 0.6263
- 0.7368
- 0.7477
- 1.0150
- 0.6934
- 0.4135
- 0.3845
- 0.2380
- 0.2853
- 0.5999
- 0.8622
- 1.2116
- 1.4921
- 1.5816
- 1.7259
- 1.6276
- 1.2422
- 0.8084
- 0.4710
- -0.3704
- -0.6427
- -0.5323
- -0.5562
- -0.3651
- -0.4356
- -0.7164
- -0.5816
- -0.4635
- -0.8456
- -0.9708
- -0.7138
- -0.7499
- -0.6941
- -0.6656
- -0.2912
- -0.1650
- 0.0774
- 0.2307
- 0.4484
- 0.4942
- 0.4653
- 0.2196
- 0.1736
- -0.1595
- -0.3918
- -0.4611
- -0.8493
- -0.7384
- -1.0604
- -1.2166
- -1.7187
- -1.6932
- -1.7830
- -1.7035
- -2.2079
- -2.3769
- -2.2511
- -2.1093
- -2.4638
- -2.4027
- -2.1313
- -1.9199
- -1.7941
- -1.4661
- -1.2269
- -1.0392
- -1.0725
- -0.7156
- -0.4778
- -0.4233
- -0.0409
- 0.1620
- 0.4280
- 0.5873
- 1.0323
- 1.3420
- 1.6902
- 2.0680
- 2.8219
- 3.2511
- 3.2930
- 3.5633
- 3.8992
- 3.6874
- 3.2849
- 3.1614
- 2.6221
- 2.5067
- 1.9223
- 1.1777
- 0.4483
- -0.0661
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- -0.9000
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- -1.0200
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- -1.1740
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- -0.9866
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- -0.2329
- 0.1493
- 0.4906
- 0.8400
- 1.0720
- 1.2648
- 1.5431
-];
-
-PIE =[
- -1.0113
- -0.8305
- 0.2332
- -0.8746
- -0.7978
- -0.9220
- -0.2487
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- 0.8791
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- 1.0997
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- 1.1927
- 0.4420
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- 0.0345
- 0.0196
- 0.3371
- 0.9379
- 1.2160
- 0.3393
- 0.5813
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- 0.5981
- -0.1523
- 0.4458
- 0.2182
- 0.9793
- 0.7562
- 1.0064
- 0.8203
- 0.6966
- 0.3352
- 0.6581
- 0.6111
- 0.9833
- 1.1991
- 0.9562
- 0.3868
- 0.2939
- 0.2471
- 0.8331
- 0.0715
- 0.3910
- 0.3301
- 0.2547
- -0.2702
- -0.2998
- -0.1953
- -0.2293
- -0.3284
- 0.0480
- -0.0374
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- -0.5745
- -0.2989
- -0.0063
- 0.0088
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- -0.4073
- 0.2674
- 0.2896
- 0.0669
- 0.1166
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- -0.2518
- -0.0562
- -0.3269
- -0.0703
- -0.1046
- -0.4888
- -0.3524
- -0.2485
- -0.5870
- -0.4546
- -0.3970
- -0.2353
- -0.0352
- -0.2171
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- -0.4322
- -0.4572
- -0.4903
- -0.4518
- -0.6435
- -0.6304
- -0.4148
- -0.2892
- -0.4318
- -0.6010
- -0.4148
- -0.4315
- -0.3531
- -0.8053
- -0.4680
- -0.4263
-];
-
-R =[
- -1.0750
- -1.1540
- -1.3682
- -1.4569
- -1.3490
- -1.4011
- -1.6486
- -1.6968
- -1.6976
- -1.2567
- -1.1392
- -0.7783
- -0.3021
- -0.0435
- 0.0066
- -0.0043
- 0.1029
- -0.0628
- -0.5358
- -0.9627
- -1.1079
- -1.0918
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- -0.0997
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- -0.3710
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- -0.2432
- 0.1098
- 0.5349
- 0.7094
- 0.8415
- 0.6226
- 0.7376
- 0.9316
- 1.4370
- 1.5853
- 1.4267
- 1.1783
- 1.2046
- 0.9689
- 0.7918
- 0.6315
- 0.5950
- 0.6853
- 0.7171
- 0.5887
- 0.4873
- 0.4027
- 0.3489
- 0.2934
- 0.3060
- 0.1741
- 0.0348
- 0.0771
- -0.1005
- -0.1518
- -0.1104
- -0.0681
- -0.0059
- 0.0256
- 0.0404
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- -0.2002
- 0.0015
- 0.1249
- 0.3738
- 0.4320
- 0.5579
- 0.8186
- 0.8727
- 0.7356
- 0.7243
- 0.8635
- 0.9058
- 0.7656
- 0.7936
- 0.8631
- 0.9074
- 0.9547
- 1.2045
- 1.0850
- 0.9178
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- 0.3178
- 0.1472
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- 0.1132
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- -0.2691
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- -0.3791
- -0.4020
- -0.4166
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- -0.4075
- -0.4311
- -0.4470
- -0.5111
- -0.6274
- -0.7261
- -0.6974
- -0.5012
-];
-
-W =[
- -14.8791
- -13.2300
- -13.5037
- -13.0249
- -11.2546
- -10.0148
- -8.8586
- -8.5739
- -7.7851
- -6.7136
- -5.5878
- -4.6881
- -3.8039
- -3.0366
- -2.7342
- -1.3135
- -0.7387
- -0.1131
- -0.2769
- 0.8696
- 1.8855
- 2.3667
- 2.4942
- 3.2049
- 3.9682
- 5.1500
- 4.7047
- 4.7827
- 5.3377
- 5.6614
- 5.2813
- 5.2967
- 5.5175
- 6.1526
- 5.6627
- 6.0694
- 6.5824
- 6.9032
- 6.7849
- 6.6896
- 6.6201
- 6.9933
- 5.8959
- 6.7419
- 6.9999
- 6.4009
- 5.5083
- 5.1054
- 5.2813
- 4.5790
- 3.9589
- 3.8599
- 3.8978
- 2.7957
- 3.2480
- 1.4634
- 1.9219
- 1.8398
- 1.9279
- 1.8316
- 1.6092
- 1.2741
- 0.2031
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- -0.1004
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- -0.5644
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- -0.5346
- 0.0652
- 0.1301
- 0.3444
- -0.3592
- 0.8096
- 0.9644
- 1.0289
- 1.2781
- 1.2298
- 2.2134
- 2.0808
- 0.4925
- 0.6506
- 0.5531
- 0.2456
- -0.5351
- -0.8183
- -0.8967
- -0.7268
- -1.0738
- -1.2844
- -1.4338
- -1.6995
- -1.7085
- -2.2889
- -2.1018
- -2.4273
- -2.4609
- -2.1407
- -2.3847
- -3.1689
- -4.5581
- -4.1027
- -4.2436
- -4.8836
- -5.9660
- -4.9971
- -5.2386
- -5.6618
-];
-
-Y =[
- -4.9347
- -4.6205
- -5.2198
- -4.5937
- -3.8015
- -3.6643
- -2.7239
- -2.7524
- -2.0634
- -1.0112
- 0.0530
- 0.7623
- 1.7927
- 2.1486
- 2.4866
- 2.1456
- 2.1671
- -0.0254
- -1.6716
- -1.9673
- -1.6109
- -1.0292
- -0.1222
- 0.7329
- 1.1234
- 2.0603
- 1.7998
- 1.4820
- 1.1732
- 1.6424
- 1.5382
- 2.1399
- 2.0127
- 2.7210
- 2.4966
- 3.5249
- 3.6237
- 4.2011
- 4.5634
- 3.3442
- 2.7761
- 1.9812
- 1.3779
- 1.4616
- 1.3029
- 0.7594
- 0.3695
- 0.0832
- -0.8118
- -1.4557
- -1.4850
- -1.2346
- -1.5696
- -1.3785
- -0.7682
- -2.0308
- -1.7778
- -1.7801
- -2.1711
- -1.7469
- -1.3413
- -1.3352
- -2.4390
- -1.2125
- -1.1695
- -1.0891
- -2.4753
- -1.3503
- -0.9412
- -0.1470
- 0.0026
- 0.1108
- 0.6890
- 1.3520
- 1.6018
- 2.0667
- 1.7625
- 2.6658
- 3.4048
- 3.2507
- 3.4251
- 3.2174
- 3.1903
- 3.3396
- 3.1358
- 2.8625
- 3.3546
- 2.4609
- 1.9534
- 0.9962
- -0.7904
- -1.1672
- -1.2586
- -1.3593
- -1.3443
- -0.9413
- -0.6023
- -0.4516
- -0.5129
- -0.8741
- -1.0784
- -1.4091
- -1.3627
- -1.5731
- -1.6037
- -1.8814
- -2.1482
- -1.3597
- -1.1855
- -1.1122
- -0.8424
- -0.9747
- -1.1385
- -1.4548
- -1.4284
- -1.4633
- -1.0621
- -0.7871
-];
diff --git a/mex/sources/estimation/tests/sweuromodel_dll.mod b/mex/sources/estimation/tests/sweuromodel_dll.mod
deleted file mode 100644
index 658dec00ade7f33ddb47b52db7b3562f4cc35c0d..0000000000000000000000000000000000000000
--- a/mex/sources/estimation/tests/sweuromodel_dll.mod
+++ /dev/null
@@ -1,182 +0,0 @@
-//options_.usePartInfo=1;
-
-var MC E EF R_KF QF CF IF YF LF PIEF WF RF R_K Q C I Y L PIE W R EE_A PIE_BAR EE_B EE_G EE_L EE_I KF K one BIGTHETA;
-
-varexo E_A E_B E_G E_L E_I ETA_R E_PIE_BAR ETA_Q ETA_P ETA_W ;
-
-parameters
-xi_e lambda_w alpha czcap beta phi_i tau sig_c hab ccs cinvs phi_y gamma_w xi_w gamma_p xi_p sig_l r_dpi
-r_pie r_dy r_y rho rho_a rho_pb rho_b rho_g rho_l rho_i LMP ;
-
-
-
-alpha=.30;
-beta=.99;
-tau=0.025;
-ccs=0.6;
-cinvs=.22; //% alpha*(tau+ctrend)/R_K R_K=ctrend/beta-1+tau
-lambda_w = 0.5;
-phi_i= 6.771;
-sig_c= 1.353;
-hab= 0.573;
-xi_w= 0.737;
-sig_l= 2.400;
-xi_p= 0.908;
-xi_e= 0.599;
-gamma_w= 0.763;
-gamma_p= 0.469;
-czcap= 0.169;
-phi_y= 1.408;
-r_pie= 1.684;
-r_dpi= 0.14;
-rho= 0.961;
-r_y= 0.099;
-r_dy= 0.159;
-rho_a= 0.823;
-rho_b= 0.855;
-rho_g= 0.949;
-rho_l= 0.889;
-rho_i= 0.927;
-rho_pb= 0.924;
-LMP = 0.0 ; //NEW.
-
-model(linear, use_dll);
- CF = (1/(1+hab))*(CF(1)+hab*CF(-1))-((1-hab)/((1+hab)*sig_c))*(RF-PIEF(1)-EE_B) ;
- 0 = alpha*R_KF+(1-alpha)*WF -EE_A ;
- PIEF = 0*one;
- IF = (1/(1+beta))* (( IF(-1) + beta*(IF(1)))+(1/phi_i)*QF)+0*ETA_Q+EE_I ;
- QF = -(RF-PIEF(1))+(1-beta*(1-tau))*((0+czcap)/czcap)*R_KF(1)+beta*(1-tau)*QF(1) +0*EE_I ;
- KF = (1-tau)*KF(-1)+tau*IF(-1) ;
- YF = (ccs*CF+cinvs*IF)+EE_G ;
-
- YF = 1*phi_y*( alpha*KF+alpha*(1/czcap)*R_KF+(1-alpha)*LF+EE_A ) ;
- WF = (sig_c/(1-hab))*(CF-hab*CF(-1)) + sig_l*LF - EE_L ;
- LF = R_KF*((1+czcap)/czcap)-WF+KF ;
- EF = EF(-1)+EF(1)-EF+(LF-EF)*((1-xi_e)*(1-xi_e*beta)/(xi_e));
-
- C = (hab/(1+hab))*C(-1)+(1/(1+hab))*C(1)-((1-hab)/((1+hab)*sig_c))*(R-PIE(1)-EE_B) ;
- I = (1/(1+beta))* (( I(-1) + beta*(I(1)))+(1/phi_i)*Q )+1*ETA_Q+1*EE_I ;
- Q = -(R-PIE(1))+(1-beta*(1-tau))*((0+czcap)/czcap)*R_K(1)+beta*(1-tau)*Q(1) +EE_I*0+0*ETA_Q ;
- K = (1-tau)*K(-1)+tau*I(-1) ;
- Y = (ccs*C+cinvs*I)+ EE_G ;
- Y = phi_y*( alpha*K+alpha*(1/czcap)*R_K+(1-alpha)*L ) +phi_y*EE_A ;
- PIE = (1/(1+beta*gamma_p))*
- (
- (beta)*(PIE(1)) +(gamma_p)*(PIE(-1))
- +((1-xi_p)*(1-beta*xi_p)/(xi_p))*(MC)
- ) + ETA_P ;
-
- MC = alpha*R_K+(1-alpha)*W -EE_A;
- W = (1/(1+beta))*(beta*W(+1)+W(-1))
- +(beta/(1+beta))*(PIE(+1))
- -((1+beta*gamma_w)/(1+beta))*(PIE)
- +(gamma_w/(1+beta))*(PIE(-1))
- -(1/(1+beta))*(((1-beta*xi_w)*(1-xi_w))/(((1+(((1+lambda_w)*sig_l)/(lambda_w))))*xi_w))*(W-sig_l*L-(sig_c/(1-hab))*(C-hab*C(-1))+EE_L)
- +ETA_W;
- L = R_K*((1+czcap)/czcap)-W+K ;
-
-// R = r_dpi*(PIE-PIE(-1))
-// +(1-rho)*(r_pie*(PIE(-1)-PIE_BAR)+r_y*(Y-YF))
-// +r_dy*(Y-YF-(Y(-1)-YF(-1)))
-// +rho*(R(-1)-PIE_BAR)
-// +PIE_BAR
-// +ETA_R;
-
-
- R =
-
-r_dpi*(PIE-PIE(-1))
-
- +(1-rho)*(r_pie*(BIGTHETA)+r_y*(Y-YF))
- +r_dy*(Y-YF-(Y(-1)-YF(-1)))
- +rho*(R(-1)-PIE_BAR)
- +PIE_BAR
- +ETA_R;
-
-
- E = E(-1)+E(1)-E+(L-E)*((1-xi_e)*(1-xi_e*beta)/(xi_e));
-
-
- EE_A = (rho_a)*EE_A(-1) + E_A;
- PIE_BAR = rho_pb*PIE_BAR(-1)+ E_PIE_BAR ;
- EE_B = rho_b*EE_B(-1) + E_B ;
- EE_G = rho_g*EE_G(-1) + E_G ;
- EE_L = rho_l*EE_L(-1) + E_L ;
- EE_I = rho_i*EE_I(-1) + E_I ;
- one = 0*one(-1) ;
-
- LMP*BIGTHETA(1) = BIGTHETA - (PIE(-1) - PIE_BAR) ;
-
-end;
-
-
-shocks;
-var E_A; stderr 0.598;
-var E_B; stderr 0.336;
-var E_G; stderr 0.325;
-var E_I; stderr 0.085;
-var E_L; stderr 3.520;
-var ETA_P; stderr 0.160;
-var ETA_W; stderr 0.289;
-var ETA_R; stderr 0.081;
-var ETA_Q; stderr 0.604;
-var E_PIE_BAR; stderr 0.017;
-end;
-
-//stoch_simul(irf=20) Y C PIE R W R_K L Q I K ;
-
-// stoch_simul generates what kind of standard errors for the shocks ?
-
-//steady;
-//check;
-//stoch_simul(periods=200,irf=20,simul_seed=3) Y C PIE MC R W R_K E L I ;
-
-//datatomfile('ddd',[]);
-
-// new syntax
-
-estimated_params;
-// PARAM NAME, INITVAL, LB, UB, PRIOR_SHAPE, PRIOR_P1, PRIOR_P2, PRIOR_P3, PRIOR_P4, JSCALE
-// PRIOR_SHAPE: BETA_PDF, GAMMA_PDF, NORMAL_PDF, INV_GAMMA_PDF
-stderr E_A,0.543,0.01,4,INV_GAMMA_PDF,0.4,2;
-stderr E_PIE_BAR,0.072,0.001,4,INV_GAMMA_PDF,0.02,10;
-stderr E_B,0.2694,0.01,4,INV_GAMMA_PDF,0.2,2;
-stderr E_G,0.3052,0.01,4,INV_GAMMA_PDF,0.3,2;
-stderr E_L,1.4575,0.1,6,INV_GAMMA_PDF,1,2;
-stderr E_I,0.1318,0.01,4,INV_GAMMA_PDF,0.1,2;
-stderr ETA_R,0.1363,0.01,4,INV_GAMMA_PDF,0.1,2;
-stderr ETA_Q,0.4842,0.01,4,INV_GAMMA_PDF,0.4,2;
-stderr ETA_P,0.1731,0.01,4,INV_GAMMA_PDF,0.15,2;
-stderr ETA_W,0.2462,0.1,4,INV_GAMMA_PDF,0.25,2;
-rho_a,.9722,.1,.9999,BETA_PDF,0.85,0.1;
-rho_pb,.85,.1,.999,BETA_PDF,0.85,0.1;
-rho_b,.7647,.1,.99,BETA_PDF,0.85,0.1;
-rho_g,.9502,.1,.9999,BETA_PDF,0.85,0.1;
-rho_l,.9542,.1,.9999,BETA_PDF,0.85,0.1;
-rho_i,.6705,.1,.99,BETA_PDF,0.85,0.1;
-phi_i,5.2083,1,15,NORMAL_PDF,4,1.5;
-sig_c,0.9817,0.25,3,NORMAL_PDF,1,0.375;
-hab,0.5612,0.3,0.95,BETA_PDF,0.7,0.1;
-xi_w,0.7661,0.3,0.9,BETA_PDF,0.75,0.05;
-sig_l,1.7526,0.5,5,NORMAL_PDF,2,0.75;
-xi_p,0.8684,0.3,0.95,BETA_PDF,0.75,0.05;
-xi_e,0.5724,0.1,0.95,BETA_PDF,0.5,0.15;
-gamma_w,0.6202,0.1,0.99,BETA_PDF,0.75,0.15;
-gamma_p,0.6638,0.1,0.99,BETA_PDF,0.75,0.15;
-czcap,0.2516,0.01,2,NORMAL_PDF,0.2,0.075;
-phi_y,1.3011,1.001,2,NORMAL_PDF,1.45,0.125;
-r_pie,1.4616,1.2,2,NORMAL_PDF,1.7,0.1;
-r_dpi,0.1144,0.01,0.5,NORMAL_PDF,0.3,0.1;
-rho,0.8865,0.5,0.99,BETA_PDF,0.8,0.10;
-r_y,0.0571,0.01,0.2,NORMAL_PDF,0.125,0.05;
-r_dy,0.2228,0.05,0.5,NORMAL_PDF,0.0625,0.05;
-end;
-
-varobs Y C I E PIE W R;
-
-//estimation(datafile=rawdata_euromodel_1,presample=40, first_obs=1, nobs=118, lik_init=2, mode_compute=1,mh_replic=0);
-estimation(datafile=rawdata_euromodel_1,presample=40, first_obs=1, nobs=118,mh_jscale=0.2,mh_replic=150000, mode_check); //
-
-
-//stoch_simul(periods=200,irf=20,simul_seed=3) Y C PIE R W R_K L Q I K ;
-
diff --git a/mex/sources/estimation/tests/test-dr.cc b/mex/sources/estimation/tests/test-dr.cc
deleted file mode 100644
index 7d9ebd17c483ed6d910847a4f44b326dd55080cf..0000000000000000000000000000000000000000
--- a/mex/sources/estimation/tests/test-dr.cc
+++ /dev/null
@@ -1,193 +0,0 @@
-/*
- * This test of DecisionRules class is based on example1.mod.
- */
-
-/*
- * Copyright (C) 2010-2011 Dynare Team
- *
- * This file is part of Dynare.
- *
- * Dynare is free software: you can redistribute it and/or modify
- * it under the terms of the GNU General Public License as published by
- * the Free Software Foundation, either version 3 of the License, or
- * (at your option) any later version.
- *
- * Dynare is distributed in the hope that it will be useful,
- * but WITHOUT ANY WARRANTY; without even the implied warranty of
- * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
- * GNU General Public License for more details.
- *
- * You should have received a copy of the GNU General Public License
- * along with Dynare. If not, see <http://www.gnu.org/licenses/>.
- */
-
-#include "DecisionRules.hh"
-
-int
-main(int argc, char **argv)
-{
- size_t endo_nbr = 6, exo_nbr = 2;
-
- std::vector<size_t> zeta_fwrd, zeta_back, zeta_mixed, zeta_static;
- // y and c are purely forward
- zeta_fwrd.push_back(0);
- zeta_fwrd.push_back(1);
- // k and a are purely backward
- zeta_back.push_back(2);
- zeta_back.push_back(3);
- // h is static
- zeta_static.push_back(4);
- // b is both backward and forward
- zeta_mixed.push_back(5);
-
- double qz_criterium = 1.000001;
-
- DecisionRules dr(endo_nbr, exo_nbr, zeta_fwrd, zeta_back, zeta_mixed,
- zeta_static, qz_criterium);
-
- double jacob_data[] = {
- 0.000000000000000,
- 0.000000000000000,
- -0.035101010101010,
- -0.975000000000000,
- 0.000000000000000,
- 0.000000000000000,
- 0.000000000000000,
- 0.000000000000000,
- 0.000000000000000,
- 0.000000000000000,
- -0.950000000000000,
- -0.025000000000000,
- 0.000000000000000,
- 0.000000000000000,
- 0.000000000000000,
- 0.000000000000000,
- -0.025000000000000,
- -0.950000000000000,
- -0.640000000000000,
- 0.000000000000000,
- 1.000000000000000,
- -1.000000000000000,
- 0.000000000000000,
- 0.000000000000000,
- 0.860681114551094,
- -13.792569659442703,
- 0.000000000000000,
- 1.000000000000000,
- 0.000000000000000,
- 0.000000000000000,
- 0.000000000000000,
- 0.034750000000000,
- 0.000000000000000,
- 1.000000000000000,
- 0.000000000000000,
- 0.000000000000000,
- 0.000000000000000,
- 0.000000000000000,
- -1.080682530956729,
- 0.000000000000000,
- 1.000000000000000,
- 0.000000000000000,
- 2.370597639417809,
- 0.000000000000000,
- -2.370597639417800,
- 0.000000000000000,
- 0.000000000000000,
- 0.000000000000000,
- 0.000000000000000,
- -11.083604432603581,
- 0.000000000000000,
- -0.277090110815090,
- 0.000000000000000,
- 1.000000000000000,
- 0.000000000000000,
- -0.356400000000000,
- 0.000000000000000,
- 0.000000000000000,
- 0.000000000000000,
- 0.000000000000000,
- 0.000000000000000,
- 13.792569659442703,
- 0.000000000000000,
- 0.000000000000000,
- 0.000000000000000,
- 0.000000000000000,
- 0.000000000000000,
- 10.698449178570606,
- 0.000000000000000,
- 0.000000000000000,
- 0.000000000000000,
- 0.000000000000000,
- 0.000000000000000,
- 0.000000000000000,
- 0.000000000000000,
- 0.000000000000000,
- -1.000000000000000,
- 0.000000000000000,
- 0.000000000000000,
- 0.000000000000000,
- 0.000000000000000,
- 0.000000000000000,
- 0.000000000000000,
- -1.000000000000000
- };
-
- MatrixView jacob_tmp(jacob_data, 6, 14, 6);
-
- Matrix jacobian(6, 14), g_y(6, 3), g_u(6, 2);
- jacobian = jacob_tmp;
-
- try
- {
- dr.compute(jacobian, g_y, g_u);
- }
- catch (GeneralizedSchurDecomposition::GSDException &e)
- {
- std::cerr << e << std::endl;
- }
- catch (DecisionRules::BlanchardKahnException &e)
- {
- std::cerr << e << std::endl;
- }
-
- Vector eig_real(6), eig_cmplx(6);
- dr.getGeneralizedEigenvalues(eig_real, eig_cmplx);
- std::cout << "Eigenvalues (real part): " << eig_real
- << "Eigenvalues (complex part): " << eig_cmplx << std::endl
- << "g_y = " << std::endl << g_y << std::endl
- << "g_u = " << std::endl << g_u;
-
- // Check the results for g_y
- double real_g_y_data[] = {
- 0.005358267364601, 1.836717147430803, 0.837085806295838,
- 0.038541607674354, 0.424582606909411, -0.318740381721598,
- 0.941816659690247, 1.419061793291772, 1.419061793291773,
- -0.000000000000000, 0.950000000000000, 0.025000000000000,
- -0.012546516642830, 0.341714987626857, 0.341714987626861,
- 0.000000000000000, 0.025000000000000, 0.950000000000000
- };
-
- MatrixView real_g_y_prime(real_g_y_data, 3, 6, 3);
- Matrix real_g_y(6, 3);
- mat::transpose(real_g_y, real_g_y_prime);
- mat::sub(real_g_y, g_y);
-
- assert(mat::nrminf(real_g_y) < 1e-13);
-
- // Check the results for g_u
- double real_g_u_data[] = {
- 1.911522267389459, 0.830839736432740,
- 0.456074274269694, -0.347518145871938,
- 1.455447993119765, 1.455447993119767,
- 1.000000000000000, 0,
- 0.350476910386520, 0.350476910386525,
- 0, 1.000000000000000
- };
-
- MatrixView real_g_u_prime(real_g_u_data, 2, 6, 2);
- Matrix real_g_u(6, 2);
- mat::transpose(real_g_u, real_g_u_prime);
- mat::sub(real_g_u, g_u);
-
- assert(mat::nrminf(real_g_u) < 1e-13);
-}
diff --git a/mex/sources/estimation/tests/testInitKalman.cc b/mex/sources/estimation/tests/testInitKalman.cc
deleted file mode 100644
index 7c1451f5cb4ba7b23589601a4c6f78c98e61c25f..0000000000000000000000000000000000000000
--- a/mex/sources/estimation/tests/testInitKalman.cc
+++ /dev/null
@@ -1,153 +0,0 @@
-/*
- * Copyright (C) 2010-2011 Dynare Team
- *
- * This file is part of Dynare.
- *
- * Dynare is free software: you can redistribute it and/or modify
- * it under the terms of the GNU General Public License as published by
- * the Free Software Foundation, either version 3 of the License, or
- * (at your option) any later version.
- *
- * Dynare is distributed in the hope that it will be useful,
- * but WITHOUT ANY WARRANTY; without even the implied warranty of
- * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
- * GNU General Public License for more details.
- *
- * You should have received a copy of the GNU General Public License
- * along with Dynare. If not, see <http://www.gnu.org/licenses/>.
- */
-
-// Test for InitializeKalmanFilter
-// Uses fs2000k2e.mod and its ..._dynamic.mexw32
-
-#include "InitializeKalmanFilter.hh"
-
-int
-main(int argc, char **argv)
-{
- if (argc < 2)
- {
- std::cerr << argv[0] << ": please provide as argument the name of the dynamic DLL generated from fs2000k2.mod (typically fs2000k2_dynamic.mex*)" << std::endl;
- exit(EXIT_FAILURE);
- }
-
- std::string modName = argv[1];
- const int npar = 7; //(int)mxGetM(mxFldp);
- const size_t n_endo = 15, n_exo = 2;
- std::vector<size_t> zeta_fwrd_arg;
- std::vector<size_t> zeta_back_arg;
- std::vector<size_t> zeta_mixed_arg;
- std::vector<size_t> zeta_static_arg;
- //std::vector<size_t>
- double qz_criterium = 1.000001; //1.0+1.0e-9;
- Vector steadyState(n_endo), deepParams(npar);
-
- double dYSparams [] = {
- 1.000199998312523,
- 0.993250551764778,
- 1.006996670195112,
- 1,
- 2.718562165733039,
- 1.007250753636589,
- 18.982191739915155,
- 0.860847884886309,
- 0.316729149714572,
- 0.861047883198832,
- 1.00853622757204,
- 0.991734328394345,
- 1.355876776121869,
- 1.00853622757204,
- 0.992853374047708
- };
-
- double vcov[] = {
- 0.001256631601, 0.0,
- 0.0, 0.000078535044
- };
-
- double dparams[] = {
- 0.3560,
- 0.9930,
- 0.0085,
- 1.0002,
- 0.1290,
- 0.6500,
- 0.0100
- };
-
- VectorView modParamsVW(dparams, npar, 1);
- deepParams = modParamsVW;
- VectorView steadyStateVW(dYSparams, n_endo, 1);
- steadyState = steadyStateVW;
- std::cout << "Vector deepParams: " << std::endl << deepParams << std::endl;
- std::cout << "Vector steadyState: " << std::endl << steadyState << std::endl;
-
- // Set zeta vectors [0:(n-1)] from Matlab indices [1:n] so that:
- // order_var = [ stat_var(:); pred_var(:); both_var(:); fwrd_var(:)];
- size_t statc[] = { 4, 5, 6, 8, 9, 10, 11, 12, 14};
- size_t back[] = {1, 7, 13};
- size_t both[] = {2};
- size_t fwd[] = { 3, 15};
- for (int i = 0; i < 9; ++i)
- zeta_static_arg.push_back(statc[i]-1);
- for (int i = 0; i < 3; ++i)
- zeta_back_arg.push_back(back[i]-1);
- for (int i = 0; i < 1; ++i)
- zeta_mixed_arg.push_back(both[i]-1);
- for (int i = 0; i < 2; ++i)
- zeta_fwrd_arg.push_back(fwd[i]-1);
-
- size_t varobs[] = {12, 11};
- std::vector<size_t> varobs_arg;
- for (size_t i = 0; i < 2; ++i)
- varobs_arg.push_back(varobs[i]-1);
-
- // Compute zeta_varobs_back_mixed
- sort(varobs_arg.begin(), varobs_arg.end());
- std::vector<size_t> zeta_back_mixed, zeta_varobs_back_mixed;
- set_union(zeta_back_arg.begin(), zeta_back_arg.end(),
- zeta_mixed_arg.begin(), zeta_mixed_arg.end(),
- back_inserter(zeta_back_mixed));
- set_union(zeta_back_mixed.begin(), zeta_back_mixed.end(),
- varobs_arg.begin(), varobs_arg.end(),
- back_inserter(zeta_varobs_back_mixed));
-
- size_t n_vbm = zeta_varobs_back_mixed.size();
-
- Matrix T(n_vbm, n_vbm), R(n_vbm, n_exo),
- RQRt(n_vbm, n_vbm), Pstar(n_vbm, n_vbm),
- Pinf(n_vbm, n_vbm), Q(n_exo);
-
- MatrixView vCovVW(vcov, n_exo, n_exo, n_exo);
- Q = vCovVW;
-
- double lyapunov_tol = 1e-16;
- int info = 0;
- size_t nobs = 2;
- Matrix yView(nobs, 192); // dummy
- yView.setAll(0.2);
- const MatrixConstView dataView(yView, 0, 0, nobs, yView.getCols()); // dummy
- Matrix yDetrendView(nobs, yView.getCols()); // dummy
- MatrixView dataDetrendView(yDetrendView, 0, 0, nobs, yDetrendView.getCols()); // dummy
-
- const Vector xparams1(0); // dummy
- double penalty = 1e8;
-
- InitializeKalmanFilter initializeKalmanFilter(modName, n_endo, n_exo,
- zeta_fwrd_arg, zeta_back_arg, zeta_mixed_arg, zeta_static_arg,
- zeta_varobs_back_mixed, qz_criterium,
- lyapunov_tol, info);
-
- std::cout << "Initialize KF with Q: " << std::endl << Q << std::endl;
-
- initializeKalmanFilter.initialize(steadyStateVW, deepParams, R, Q, RQRt, T, Pstar, Pinf,
- penalty, dataView, dataDetrendView, info);
-
- std::cout << "Matrix T: " << std::endl << T << std::endl;
- std::cout << "Matrix R: " << std::endl << R << std::endl;
- std::cout << "Matrix RQRt: " << std::endl << RQRt << std::endl;
- std::cout << "Matrix Pstar: " << std::endl << Pstar << std::endl;
- std::cout << "Matrix Pinf: " << std::endl << Pinf << std::endl;
-
-}
-
diff --git a/mex/sources/estimation/tests/testKalman.cc b/mex/sources/estimation/tests/testKalman.cc
deleted file mode 100644
index 1b3e8156a274be1a29cc5b8c8db762c401193a39..0000000000000000000000000000000000000000
--- a/mex/sources/estimation/tests/testKalman.cc
+++ /dev/null
@@ -1,136 +0,0 @@
-/*
- * Copyright (C) 2010-2011 Dynare Team
- *
- * This file is part of Dynare.
- *
- * Dynare is free software: you can redistribute it and/or modify
- * it under the terms of the GNU General Public License as published by
- * the Free Software Foundation, either version 3 of the License, or
- * (at your option) any later version.
- *
- * Dynare is distributed in the hope that it will be useful,
- * but WITHOUT ANY WARRANTY; without even the implied warranty of
- * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
- * GNU General Public License for more details.
- *
- * You should have received a copy of the GNU General Public License
- * along with Dynare. If not, see <http://www.gnu.org/licenses/>.
- */
-
-// Test for InitializeKalmanFilter
-// Uses fs2000k2e.mod and its ..._dynamic.mexw32
-
-#include "KalmanFilter.hh"
-
-int
-main(int argc, char **argv)
-{
- if (argc < 2)
- {
- std::cerr << argv[0] << ": please provide as argument the name of the dynamic DLL generated from fs2000k2.mod (typically fs2000k2_dynamic.mex*)" << std::endl;
- exit(EXIT_FAILURE);
- }
-
- std::string modName = argv[1];
- const int npar = 7; //(int)mxGetM(mxFldp);
- const size_t n_endo = 15, n_exo = 2;
- std::vector<size_t> zeta_fwrd_arg;
- std::vector<size_t> zeta_back_arg;
- std::vector<size_t> zeta_mixed_arg;
- std::vector<size_t> zeta_static_arg;
- //std::vector<size_t>
- double qz_criterium = 1.000001; //1.0+1.0e-9;
- Vector steadyState(n_endo), deepParams(npar);
-
- double dYSparams [] = {
- 1.000199998312523,
- 0.993250551764778,
- 1.006996670195112,
- 1,
- 2.718562165733039,
- 1.007250753636589,
- 18.982191739915155,
- 0.860847884886309,
- 0.316729149714572,
- 0.861047883198832,
- 1.00853622757204,
- 0.991734328394345,
- 1.355876776121869,
- 1.00853622757204,
- 0.992853374047708
- };
-
- double vcov[] = {
- 0.001256631601, 0.0,
- 0.0, 0.000078535044
- };
-
- double dparams[] = {
- 0.3560,
- 0.9930,
- 0.0085,
- 1.0002,
- 0.1290,
- 0.6500,
- 0.0100
- };
-
- VectorView modParamsVW(dparams, npar, 1);
- deepParams = modParamsVW;
- VectorView steadyStateVW(dYSparams, n_endo, 1);
- steadyState = steadyStateVW;
- std::cout << "Vector deepParams: " << std::endl << deepParams << std::endl;
- std::cout << "Vector steadyState: " << std::endl << steadyState << std::endl;
-
- // Set zeta vectors [0:(n-1)] from Matlab indices [1:n] so that:
- // order_var = [ stat_var(:); pred_var(:); both_var(:); fwrd_var(:)];
- size_t statc[] = { 4, 5, 6, 8, 9, 10, 11, 12, 14};
- size_t back[] = {1, 7, 13};
- size_t both[] = {2};
- size_t fwd[] = { 3, 15};
- for (int i = 0; i < 9; ++i)
- zeta_static_arg.push_back(statc[i]-1);
- for (int i = 0; i < 3; ++i)
- zeta_back_arg.push_back(back[i]-1);
- for (int i = 0; i < 1; ++i)
- zeta_mixed_arg.push_back(both[i]-1);
- for (int i = 0; i < 2; ++i)
- zeta_fwrd_arg.push_back(fwd[i]-1);
-
- size_t nobs = 2;
- size_t varobs[] = {12, 11};
- std::vector<size_t> varobs_arg;
- for (size_t i = 0; i < nobs; ++i)
- varobs_arg.push_back(varobs[i]-1);
-
- Matrix Q(n_exo), H(nobs);
- H.setAll(0.0);
-
- MatrixView vCovVW(vcov, n_exo, n_exo, n_exo);
- Q = vCovVW;
- std::cout << "Matrix Q: " << std::endl << Q << std::endl;
-
- double lyapunov_tol = 1e-16;
- double riccati_tol = 1e-16;
- int info = 0;
- Matrix yView(nobs, 192); // dummy
- yView.setAll(0.2);
- const MatrixConstView dataView(yView, 0, 0, nobs, yView.getCols()); // dummy
- Matrix yDetrendView(nobs, yView.getCols()); // dummy
- MatrixView dataDetrendView(yDetrendView, 0, 0, nobs, yDetrendView.getCols()); // dummy
- Vector vll(yView.getCols());
- VectorView vwll(vll, 0, vll.getSize());
-
- double penalty = 1e8;
-
- KalmanFilter kalman(modName, n_endo, n_exo,
- zeta_fwrd_arg, zeta_back_arg, zeta_mixed_arg, zeta_static_arg, qz_criterium,
- varobs_arg, riccati_tol, lyapunov_tol, info);
-
- size_t start = 0, period = 0;
- double ll = kalman.compute(dataView, steadyStateVW, Q, H, deepParams,
- vwll, dataDetrendView, start, period, penalty, info);
-
- std::cout << "ll: " << std::endl << ll << std::endl;
-}
-
diff --git a/mex/sources/estimation/tests/testModelSolution.cc b/mex/sources/estimation/tests/testModelSolution.cc
deleted file mode 100644
index 45b20d83115bb05ec1b8fd99cea30c6635c7af7e..0000000000000000000000000000000000000000
--- a/mex/sources/estimation/tests/testModelSolution.cc
+++ /dev/null
@@ -1,99 +0,0 @@
-/*
- * Copyright (C) 2010-2011 Dynare Team
- *
- * This file is part of Dynare.
- *
- * Dynare is free software: you can redistribute it and/or modify
- * it under the terms of the GNU General Public License as published by
- * the Free Software Foundation, either version 3 of the License, or
- * (at your option) any later version.
- *
- * Dynare is distributed in the hope that it will be useful,
- * but WITHOUT ANY WARRANTY; without even the implied warranty of
- * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
- * GNU General Public License for more details.
- *
- * You should have received a copy of the GNU General Public License
- * along with Dynare. If not, see <http://www.gnu.org/licenses/>.
- */
-
-// Test for ModelSolution
-// Uses fs2000k2.mod and its ..._dynamic.mexw32
-
-#include "ModelSolution.hh"
-
-int
-main(int argc, char **argv)
-{
- if (argc < 2)
- {
- std::cerr << argv[0] << ": please provide as argument the name of the dynamic DLL generated from fs2000k2.mod (typically fs2000k2_dynamic.mex*)" << std::endl;
- exit(EXIT_FAILURE);
- }
-
- std::string modName = argv[1];
- const int npar = 7;
- const size_t n_endo = 15, n_exo = 2;
- std::vector<size_t> zeta_fwrd_arg;
- std::vector<size_t> zeta_back_arg;
- std::vector<size_t> zeta_mixed_arg;
- std::vector<size_t> zeta_static_arg;
- double qz_criterium = 1.0+1.0e-9;
- Vector deepParams(npar);
-
- double dYSparams [] = {
- 1.0110, 2.2582, 0.4477, 1.0000,
- 4.5959, 1.0212, 5.8012, 0.8494,
- 0.1872, 0.8604, 1.0030, 1.0080,
- 0.5808, 1.0030, 2.2093
- };
- double vcov[] = {
- 0.1960e-3, 0.0,
- 0.0, 0.0250e-3
- };
- int nVCVpar = 2;
- MatrixView vCovVW(vcov, nVCVpar, nVCVpar, nVCVpar);
- Matrix vCov(nVCVpar, nVCVpar);
- vCov = vCovVW;
-
- double dparams[] = { 0.3300,
- 0.9900,
- 0.0030,
- 1.0110,
- 0.7000,
- 0.7870,
- 0.0200};
-
- VectorView modParamsVW(dparams, npar, 1);
- deepParams = modParamsVW;
- VectorView steadyState(dYSparams, n_endo, 1);
- std::cout << "Vector deepParams: " << std::endl << deepParams << std::endl;
- std::cout << "Matrix vCov: " << std::endl << vCov << std::endl;
- std::cout << "Vector steadyState: " << std::endl << steadyState << std::endl;
-
- // Set zeta vectors [0:(n-1)] from Matlab indices [1:n]
- //order_var = [ stat_var(:); pred_var(:); both_var(:); fwrd_var(:)];
- size_t statc[] = { 4, 5, 6, 8, 9, 10, 11, 12, 14};
- size_t back[] = {1, 7, 13};
- size_t both[] = {2};
- size_t fwd[] = { 3, 15};
- for (int i = 0; i < 9; ++i)
- zeta_static_arg.push_back(statc[i]-1);
- for (int i = 0; i < 3; ++i)
- zeta_back_arg.push_back(back[i]-1);
- for (int i = 0; i < 1; ++i)
- zeta_mixed_arg.push_back(both[i]-1);
- for (int i = 0; i < 2; ++i)
- zeta_fwrd_arg.push_back(fwd[i]-1);
-
- Matrix ghx(n_endo, zeta_back_arg.size() + zeta_mixed_arg.size());
- Matrix ghu(n_endo, n_exo);
-
- ModelSolution modelSolution(modName, n_endo, n_exo,
- zeta_fwrd_arg, zeta_back_arg, zeta_mixed_arg, zeta_static_arg, qz_criterium);
-
- modelSolution.compute(steadyState, deepParams, ghx, ghu);
-
- std::cout << "Matrix ghx: " << std::endl << ghx << std::endl;
- std::cout << "Matrix ghu: " << std::endl << ghu << std::endl;
-}
diff --git a/mex/sources/estimation/tests/testPDF.cc b/mex/sources/estimation/tests/testPDF.cc
deleted file mode 100644
index 70bdeba9f94f63d88604bbce9c8f1911938486d4..0000000000000000000000000000000000000000
--- a/mex/sources/estimation/tests/testPDF.cc
+++ /dev/null
@@ -1,76 +0,0 @@
-/*
- * Copyright (C) 2009-2011 Dynare Team
- *
- * This file is part of Dynare.
- *
- * Dynare is free software: you can redistribute it and/or modify
- * it under the terms of the GNU General Public License as published by
- * the Free Software Foundation, either version 3 of the License, or
- * (at your option) any later version.
- *
- * Dynare is distributed in the hope that it will be useful,
- * but WITHOUT ANY WARRANTY; without even the implied warranty of
- * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
- * GNU General Public License for more details.
- *
- * You should have received a copy of the GNU General Public License
- * along with Dynare. If not, see <http://www.gnu.org/licenses/>.
- */
-
-// test for Prior pdfs and basic random number generators
-
-#include "Prior.hh"
-
-int
-main(int argc, char **argv)
-{
- BetaPrior bp(0.1, 0.1, 0.0, 1.0, 5.0, 1.0);
- double pdf = bp.pdf(0.5);
- std::cout << "beta pdf of 5,1, 0.5: " << std::setw(13) << pdf << std::endl;
- BetaPrior *bpp = new BetaPrior(0.1, 0.1, 0.0, 1.0, 1.0, 5.0);
- Prior *pp = bpp;
- pdf = (*pp).pdf(0.1);
- std::cout << "Parent (Beta) pdf of 1,5, 0.1: " << std::setw(13) << pdf << std::endl;
-
- GammaPrior *gpp = new GammaPrior(0.1, 0.1, 0.0, 1.0, 1.0, 5.0);
- pp = gpp;
- pdf = (*pp).pdf(0.1);
- std::cout << "Parent (Gamma) pdf of 1,5, 0.1: " << std::setw(13) << pdf << std::endl;
-
- UniformPrior up(5, 2, 1, 10, 20, 100);
- std::cout << std::endl << "Uniform prior (5,2, 1,10,20,100): " << std::endl;
- double ur, updf;
- for (int i = 0; i < 10; i++)
- {
- ur = up.drand();
- updf = up.pdf(ur);
- std::cout << "Uniform pdf of : " << ur << " = " << updf << std::endl;
- }
-
- GaussianPrior gp(5, 2, 1, 10, 20, 100);
- std::cout << std::endl << "Gaussian prior (5,2, 1,10,20,100): " << std::endl;
- for (int i = 0; i < 10; i++)
- {
- ur = gp.drand();
- updf = gp.pdf(ur);
- std::cout << "Gaussian pdf of : " << ur << " = " << updf << std::endl;
- }
-
- UniformPrior up2(5, 2, 1, 100, 20, 100);
- std::cout << std::endl << "Uniform prior (5,2, 1,100,20,100): " << std::endl;
- for (int i = 0; i < 10; i++)
- {
- ur = up2.drand();
- updf = up2.pdf(ur);
- std::cout << "Uniform pdf of : " << ur << " = " << updf << std::endl;
- }
-
- GaussianPrior gp2(5, 2, 1, 100, 5, 2);
- std::cout << std::endl << "Gaussian prior (5,2, 1,100,5,2): " << std::endl;
- for (int i = 0; i < 10; i++)
- {
- ur = gp2.drand();
- updf = gp2.pdf(ur);
- std::cout << "Gaussian pdf of : " << ur << " = " << updf << std::endl;
- }
-};
diff --git a/mex/sources/estimation/utils/dynamic_dll.cc b/mex/sources/estimation/utils/dynamic_dll.cc
deleted file mode 100644
index 495e0bae4966d7ba42449d6bc7748280ef5b01c2..0000000000000000000000000000000000000000
--- a/mex/sources/estimation/utils/dynamic_dll.cc
+++ /dev/null
@@ -1,92 +0,0 @@
-/*
- * Copyright (C) 2010-2012 Dynare Team
- *
- * This file is part of Dynare.
- *
- * Dynare is free software: you can redistribute it and/or modify
- * it under the terms of the GNU General Public License as published by
- * the Free Software Foundation, either version 3 of the License, or
- * (at your option) any later version.
- *
- * Dynare is distributed in the hope that it will be useful,
- * but WITHOUT ANY WARRANTY; without even the implied warranty of
- * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
- * GNU General Public License for more details.
- *
- * You should have received a copy of the GNU General Public License
- * along with Dynare. If not, see <http://www.gnu.org/licenses/>.
- */
-
-#include "dynamic_dll.hh"
-
-#include <sstream>
-
-using namespace std;
-
-DynamicModelDLL::DynamicModelDLL(const std::string &dynamicDllFile, size_t n_exog_arg) throw (TSException) :
- n_exog(n_exog_arg)
-{
- std::string fName;
-#if !defined(__CYGWIN32__) && !defined(_WIN32)
- if (dynamicDllFile[0] != '/')
- fName = "./";
-#endif
- fName += dynamicDllFile;
-
- try
- {
-#if defined(__CYGWIN32__) || defined(_WIN32)
- dynamicHinstance = LoadLibrary(fName.c_str());
- if (dynamicHinstance == NULL)
- throw 1;
- Dynamic = (DynamicFn) GetProcAddress(dynamicHinstance, "Dynamic");
- if (Dynamic == NULL)
- {
- FreeLibrary(dynamicHinstance); // Free the library
- throw 2;
- }
-#else // Linux or Mac
- dynamicHinstance = dlopen(fName.c_str(), RTLD_NOW);
- if ((dynamicHinstance == NULL) || dlerror())
- {
- cerr << dlerror() << endl;
- throw 1;
- }
- Dynamic = (DynamicFn) dlsym(dynamicHinstance, "Dynamic");
- if ((Dynamic == NULL) || dlerror())
- {
- dlclose(dynamicHinstance); // Free the library
- cerr << dlerror() << endl;
- throw 2;
- }
-#endif
-
- }
- catch (int i)
- {
- std::ostringstream msg;
- msg << "Error when loading " << fName << " (";
- if (i == 1)
- msg << "can't dynamically load the file";
- if (i == 2)
- msg << "can't locate the 'Dynamic' symbol";
- msg << ")";
- throw TSException(__FILE__, __LINE__, msg.str());
- }
- catch (...)
- {
- throw TSException(__FILE__, __LINE__, std::string("Can't find Dynamic function in ") + fName);
- }
-}
-
-DynamicModelDLL::~DynamicModelDLL()
-{
-#if defined(__CYGWIN32__) || defined(_WIN32)
- bool result = FreeLibrary(dynamicHinstance);
- if (result == 0)
- throw TSException(__FILE__, __LINE__, std::string("Can't free the *_dynamic DLL"));
-#else
- dlclose(dynamicHinstance);
-#endif
-}
-
diff --git a/mex/sources/estimation/utils/dynamic_dll.hh b/mex/sources/estimation/utils/dynamic_dll.hh
deleted file mode 100644
index dfb4d8b19fb69cc4e540bb321d8c42600e63f6c6..0000000000000000000000000000000000000000
--- a/mex/sources/estimation/utils/dynamic_dll.hh
+++ /dev/null
@@ -1,69 +0,0 @@
-/*
- * Copyright (C) 2010-2012 Dynare Team
- *
- * This file is part of Dynare.
- *
- * Dynare is free software: you can redistribute it and/or modify
- * it under the terms of the GNU General Public License as published by
- * the Free Software Foundation, either version 3 of the License, or
- * (at your option) any later version.
- *
- * Dynare is distributed in the hope that it will be useful,
- * but WITHOUT ANY WARRANTY; without even the implied warranty of
- * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
- * GNU General Public License for more details.
- *
- * You should have received a copy of the GNU General Public License
- * along with Dynare. If not, see <http://www.gnu.org/licenses/>.
- */
-
-#if defined(_WIN32) || defined(__CYGWIN32__)
-# ifndef NOMINMAX
-# define NOMINMAX // Do not define "min" and "max" macros
-# endif
-# include <windows.h>
-#else
-# include <dlfcn.h> // unix/linux DLL (.so) handling routines
-#endif
-
-#include <string>
-#include "Matrix.hh"
-
-#include "ts_exception.h"
-
-// <model>_Dynamic DLL pointer
-typedef void (*DynamicFn)
-(const double *y, const double *x, int nb_row_x, const double *params, const double *steady_state,
- int it_, double *residual, double *g1, double *g2, double *g3);
-
-/**
- * creates pointer to Dynamic function inside <model>_dynamic.dll
- * and handles calls to it.
- **/
-class DynamicModelDLL
-{
-private:
- DynamicFn Dynamic; // pointer to the Dynamic function in DLL
- const size_t n_exog; // no of exogenous
-#if defined(_WIN32) || defined(__CYGWIN32__)
- HINSTANCE dynamicHinstance; // DLL instance pointer in Windows
-#else
- void *dynamicHinstance; // and in Linux or Mac
-#endif
-
-public:
- // construct and load Dynamic model DLL
- DynamicModelDLL(const std::string &dynamicDllFile, size_t n_exog_arg) throw (TSException);
- virtual ~DynamicModelDLL();
-
- //! evaluate Dynamic model DLL
- void eval(const Vector &y, const Matrix &x, const Vector ¶ms, VectorView &ySteady,
- Vector &residual, Matrix *g1, Matrix *g2, Matrix *g3) throw (TSException);
- template<class VEC>
- void eval(const Vector &y, const Matrix &x, const VectorView &modParams, VEC &ySteady,
- Vector &residual, Matrix *g1, Matrix *g2, Matrix *g3) throw (TSException)
- {
- Dynamic(y.getData(), x.getData(), 1, modParams.getData(), ySteady.getData(), 0, residual.getData(),
- g1 == NULL ? NULL : g1->getData(), g2 == NULL ? NULL : g2->getData(), g3 == NULL ? NULL : g3->getData());
- };
-};
diff --git a/mex/sources/estimation/utils/ts_exception.h b/mex/sources/estimation/utils/ts_exception.h
deleted file mode 100644
index b0f8ca71a0c49e0f243765ad7deb8e323fa0c34e..0000000000000000000000000000000000000000
--- a/mex/sources/estimation/utils/ts_exception.h
+++ /dev/null
@@ -1,73 +0,0 @@
-/*
- * Copyright (C) 2010-2011 Dynare Team
- *
- * This file is part of Dynare.
- *
- * Dynare is free software: you can redistribute it and/or modify
- * it under the terms of the GNU General Public License as published by
- * the Free Software Foundation, either version 3 of the License, or
- * (at your option) any later version.
- *
- * Dynare is distributed in the hope that it will be useful,
- * but WITHOUT ANY WARRANTY; without even the implied warranty of
- * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
- * GNU General Public License for more details.
- *
- * You should have received a copy of the GNU General Public License
- * along with Dynare. If not, see <http://www.gnu.org/licenses/>.
- */
-
-/* derived from c++kalman_filter library by O. Kamenik */
-
-#ifndef TS_EXCEPTION_H
-#define TS_EXCEPTION_H
-
-#include <stdio.h>
-#include <string>
-
-#if defined(MATLAB_MEX_FILE) || defined(OCTAVE_MEX_FILE)
-# include "mex.h"
-#endif
-
-#define TS_RAISE(mes) \
- throw TSException(__FILE__, __LINE__, mes);
-
-#define TS_RAISE_IF(expr, mes) \
- if (expr) throw TSException(__FILE__, __LINE__, mes);
-
-class TSException
-{
- std::string fname; //char fname[50];
- int lnum;
- std::string message; // char message[500];
-public:
- TSException(const char *f, int l, const std::string &mes)
- {
- fname = std::string(f); // strncpy(fname,f,50);fname[49]= '\0';
- message = mes; //strncpy(message,mes,500);message[499]= '\0';
- lnum = l;
- }
- virtual
- ~TSException()
- {
- };
-
- virtual void
- print() const
- {
- printf("At %s:%d:%s\n", fname.c_str(), lnum, message.c_str());
-#if defined(MATLAB_MEX_FILE) || defined(OCTAVE_MEX_FILE)
- mexPrintf("At %s:%d:%s\n", fname.c_str(), lnum, message.c_str());
-#endif
- }
-
- virtual const std::string
- getMessage() const
- {
- return message;
- }
-};
-
-;
-#endif
-