diff --git a/m4/ax_mexopts.m4 b/m4/ax_mexopts.m4
index a676a79c0113f4fbbc803757e5bc1f56ad57b1f5..69567864838b5abdceb0e32bc0c79e8651f7e777 100644
--- a/m4/ax_mexopts.m4
+++ b/m4/ax_mexopts.m4
@@ -1,4 +1,4 @@
-dnl Copyright (C) 2009-2011 Dynare Team
+dnl Copyright (C) 2009-2012 Dynare Team
dnl
dnl This file is part of Dynare.
dnl
@@ -62,7 +62,7 @@ case ${MATLAB_ARCH} in
ax_mexopts_ok="yes"
;;
maci | maci64)
- SDKROOT='/Developer/SDKs/MacOSX10.6.sdk'
+ SDKROOT='/Applications/Xcode.app/Contents/Developer/Platforms/MacOSX.platform/Developer/SDKs/MacOSX10.6.sdk'
MACOSX_DEPLOYMENT_TARGET='10.6'
if test "${MATLAB_ARCH}" = "maci"; then
ARCHS='i386'
diff --git a/matlab/DsgeVarLikelihood.m b/matlab/DsgeVarLikelihood.m
index 840842cef89a46fcd4534994a5248167574fe75f..c00c4e92cb3ab6bb198675ae1a978ac65cd00f64 100644
--- a/matlab/DsgeVarLikelihood.m
+++ b/matlab/DsgeVarLikelihood.m
@@ -35,7 +35,9 @@ function [fval,grad,hess,exit_flag,info,PHI,SIGMAu,iXX,prior] = DsgeVarLikelihoo
% along with Dynare. If not, see <http://www.gnu.org/licenses/>.
% Declaration of the persistent variables.
-persistent penalty dsge_prior_weight_idx
+persistent dsge_prior_weight_idx
+
+penalty = BayesInfo.penalty;
grad=[];
hess=[];
@@ -46,16 +48,6 @@ SIGMAu = [];
iXX = [];
prior = [];
-% Initialization of the penalty
-if ~nargin || isempty(penalty)
- penalty = 1e8;
- if ~nargin, return, end
-end
-if nargin==1
- penalty = xparam1;
- return
-end
-
% Initialization of of the index for parameter dsge_prior_weight in Model.params.
if isempty(dsge_prior_weight_idx)
dsge_prior_weight_idx = strmatch('dsge_prior_weight',Model.param_names);
diff --git a/matlab/cmaes.m b/matlab/cmaes.m
index a2ef613c07588427fa6615fa7bf38c3461d1ee41..c0b6d215c6da3312b283408d981bfa78fc69ff9b 100644
--- a/matlab/cmaes.m
+++ b/matlab/cmaes.m
@@ -644,11 +644,11 @@ else % flgresume
end
% initialize random number generator
- if ischar(opts.Seed)
- randn('state', eval(opts.Seed)); % random number generator state
- else
- randn('state', opts.Seed);
- end
+% $$$ if ischar(opts.Seed)
+% $$$ randn('state', eval(opts.Seed)); % random number generator state
+% $$$ else
+% $$$ randn('state', opts.Seed);
+% $$$ end
%qqq
% load(opts.SaveFilename, 'startseed');
% randn('state', startseed);
diff --git a/matlab/dsge_likelihood.m b/matlab/dsge_likelihood.m
index 0b770a0d4738b1d982c0c7a0194f1d966429e5ca..245eb66fddfe58a34dd9b94b4ece646a65e93ff5 100644
--- a/matlab/dsge_likelihood.m
+++ b/matlab/dsge_likelihood.m
@@ -130,22 +130,7 @@ function [fval,DLIK,Hess,exit_flag,ys,trend_coeff,info,Model,DynareOptions,Bayes
% AUTHOR(S) stephane DOT adjemian AT univ DASH lemans DOT FR
-% Declaration of the penalty as a persistent variable.
-
-% Persistent variable 'penalty' is used to compute an endogenous penalty to
-% the value 'fval' when various conditions are encountered. These conditions
-% set also 'exit_flag' equal to 0 instead of 1. It is only when
-% dsge_likelihood() is called by an optimizer called by
-% dynare_estimation_1() that 'exit_flag' is ignored and penalized 'fval' is
-% actually used.
-% In that case, 'penalty' is properly initialized, at the very end of the
-% present function, by a call to dsge_likelihood() made in
-% initial_estimation_checks(). If a condition triggers exit_flag ==
-% 0, initial_estimation_checks() triggers an error.
-% In summary, an initial call to the present function, without triggering
-% any condition, guarantees that 'penalty' is properly initialized when needed.
-
-persistent penalty
+penalty = BayesInfo.penalty;
% Initialization of the returned variables and others...
fval = [];
@@ -568,16 +553,16 @@ if analytic_derivation,
if full_Hess
DTj = DT(:,:,j+offset);
DPj = dum;
- for i=1:j,
- DTi = DT(:,:,i+offset);
- DPi = DP(:,:,i+offset);
- D2Tij = D2T(:,:,i,j);
- D2Omij = D2Om(:,:,i,j);
+ for i=1:j+offset,
+ DTi = DT(:,:,i);
+ DPi = DP(:,:,i);
+ D2Tij = D2T(:,:,i,j+offset);
+ D2Omij = D2Om(:,:,i,j+offset);
tmp = D2Tij*Pstar*T' + T*Pstar*D2Tij' + DTi*DPj*T' + DTj*DPi*T' + T*DPj*DTi' + T*DPi*DTj' + DTi*Pstar*DTj' + DTj*Pstar*DTi' + D2Omij;
dum = lyapunov_symm(T,tmp,DynareOptions.qz_criterium,DynareOptions.lyapunov_complex_threshold);
dum(abs(dum)<1.e-12) = 0;
- D2P(:,:,i+offset,j+offset) = dum;
- D2P(:,:,j+offset,i+offset) = dum;
+ D2P(:,:,i,j+offset) = dum;
+ D2P(:,:,j+offset,i) = dum;
end
end
end
@@ -771,9 +756,6 @@ end
% Update DynareOptions.kalman_algo.
DynareOptions.kalman_algo = kalman_algo;
-% Update the penalty.
-penalty = fval;
-
if analytic_derivation==0 && nargout==2,
lik=lik(start:end,:);
DLIK=[-lnprior; lik(:)];
diff --git a/matlab/k_order_pert.m b/matlab/k_order_pert.m
index fe0973964e84307923b047134b364a4a7866dba7..0fb2355ecf4c44cf4f0c9a8651fa1745a7f21568 100644
--- a/matlab/k_order_pert.m
+++ b/matlab/k_order_pert.m
@@ -159,7 +159,7 @@ for i=1:n1
xx = x(:,m);
y(:,(i-1)*n1*n2+(j-1)*n2+k) = xx;
if j ~= i
- y(:,(j-1)*n1*n2+(i-1)*n2+i) = xx;
+ y(:,(j-1)*n1*n2+(i-1)*n2+k) = xx;
end
end
end
diff --git a/matlab/k_order_perturbation.m b/matlab/k_order_perturbation.m
new file mode 100644
index 0000000000000000000000000000000000000000..566a281175b3960fb38cc038425cb6a7c4e7befb
--- /dev/null
+++ b/matlab/k_order_perturbation.m
@@ -0,0 +1,53 @@
+% [err, g_0, g_1, g_2, g_3, derivs] = k_order_perturbation(dr,DynareModel,DynareOptions)
+% computes a k_order_petrubation solution for k=1,2,3
+%
+% INPUTS
+% dr: struct describing the reduced form solution of the model.
+% DynareModel: struct jobs's parameters
+% DynareOptions: struct job's options
+%
+% OUTPUTS
+% err: double err code (currently unused)
+% g_0: vector dynare++ output. Constant effect of future volatility (in
+% dr.order_var order) on the decision rule
+% (=ghs2/2). Contains zero when order of
+% approximation is 1.
+% g_1: matrix dynare++ output. First order Taylor coefficients
+% of decision rule. When order of approximation
+% is 3, the. Contains both the effect of
+% state endogenous variable and shocks. The rows
+% are in dr.order_var order. The columns are in
+% dr.order_var order of state endogenous
+% variables and shocks
+% g_2: matrix dynare++ output. Second order Taylor coefficients of decision
+% rule. Contains both the effect of state endogenous
+% variable and shocks. The rows are in dr.order_var
+% order. Each row corresponds to the vectorized
+% version of the lower triangle of the Hessian
+% matrix. The Taylor coefficient (1/2) is
+% included. The columns of the Hessian matrix are in
+% dr.order_var order of state endogenous variables
+% and shocks
+% g_3: matrix dynare++ output. Third order Taylor coefficients of decision
+% rule. Contains both the effect of state endogenous
+% variable and shocks. The rows are in dr.order_var
+% order. Each row corresponds to the vectorized
+% version of the 3rd order derivatives tensor where each
+% combination of variables appears only once.
+% The Taylor coefficient (1/6) is
+% included. Inside the tensor, the variables are in
+% dr.order_var order of state endogenous variables
+% and shocks
+% derivs struct contains the original derivatives of the
+% decision function (ghx, ghu, ghxx, ghxu, ghuu,
+% ghs2, ghxxx, ghxxu, ghxuu,ghuuu, ghxss, ghuss),
+% keeping the effect of future volatility
+% separate (in ghs2, ghxss and ghuss). The
+% derivatives matrices contain full versions of
+% the Hessian matrices and 3rd order
+% tensor. Symmetric derivatives are repeated. The
+% Taylor coefficients (1/2 and 1/6) aren't
+% included.
+% k_order_peturbation is a compiled MEX function. It's source code is in
+% dynare/mex/sources/k_order_perturbation.cc and it uses code provided by
+% dynare++
diff --git a/matlab/metropolis_hastings_initialization.m b/matlab/metropolis_hastings_initialization.m
index 80c2f3532a809cd39a3c376ab98e134a5775a37c..2d6e7f07d14ecfff5e8e5961f21296457b1c9713 100644
--- a/matlab/metropolis_hastings_initialization.m
+++ b/matlab/metropolis_hastings_initialization.m
@@ -180,9 +180,6 @@ if ~options_.load_mh_file && ~options_.mh_recover
% separate initializaton for each chain
JSUM = 0;
for j=1:nblck,
- JSUM = JSUM + sum(100*clock);
- randn('state',JSUM);
- rand('state',JSUM);
record.Seeds(j).Normal = randn('state');
record.Seeds(j).Unifor = rand('state');
end
diff --git a/mex/build/matlab/configure.ac b/mex/build/matlab/configure.ac
index 4a3f115d79d463506c0a6457f20042f1971fd699..ca948b4dba099f07da4484df7401bc7c7209d785 100644
--- a/mex/build/matlab/configure.ac
+++ b/mex/build/matlab/configure.ac
@@ -1,6 +1,6 @@
dnl Process this file with autoconf to produce a configure script.
-dnl Copyright (C) 2009-2011 Dynare Team
+dnl Copyright (C) 2009-2012 Dynare Team
dnl
dnl This file is part of Dynare.
dnl
@@ -17,7 +17,7 @@ dnl
dnl You should have received a copy of the GNU General Public License
dnl along with Dynare. If not, see <http://www.gnu.org/licenses/>.
-AC_PREREQ([2.61])
+AC_PREREQ([2.62])
AC_INIT([dynare], [4.4-unstable])
AC_CONFIG_SRCDIR([configure.ac])
AM_INIT_AUTOMAKE([-Wall -Werror foreign])
diff --git a/mex/build/octave/configure.ac b/mex/build/octave/configure.ac
index 34855798155da65422b3d43aaead3a97fbdbeaed..da3c6e2ac7e6e0ada7ace30c78a3a899ffc50c7f 100644
--- a/mex/build/octave/configure.ac
+++ b/mex/build/octave/configure.ac
@@ -1,6 +1,6 @@
dnl Process this file with autoconf to produce a configure script.
-dnl Copyright (C) 2009-2011 Dynare Team
+dnl Copyright (C) 2009-2012 Dynare Team
dnl
dnl This file is part of Dynare.
dnl
@@ -17,7 +17,7 @@ dnl
dnl You should have received a copy of the GNU General Public License
dnl along with Dynare. If not, see <http://www.gnu.org/licenses/>.
-AC_PREREQ([2.61])
+AC_PREREQ([2.62])
AC_INIT([dynare], [4.4-unstable])
AC_CONFIG_SRCDIR([configure.ac])
AM_INIT_AUTOMAKE([-Wall -Werror foreign])
diff --git a/mex/sources/k_order_perturbation/k_order_perturbation.cc b/mex/sources/k_order_perturbation/k_order_perturbation.cc
index 59100d23c99fee1f160fe2bf5f690c8d59e462b7..fba8b8ec4462b9ab0dbc06bae6f99e3011a2b9e6 100644
--- a/mex/sources/k_order_perturbation/k_order_perturbation.cc
+++ b/mex/sources/k_order_perturbation/k_order_perturbation.cc
@@ -260,8 +260,6 @@ extern "C" {
// run stochastic steady
app.walkStochSteady();
- app.get_rule_ders()->print();
-
/* Write derivative outputs into memory map */
map<string, ConstTwoDMatrix> mm;
app.getFoldDecisionRule().writeMMap(mm, string());