From f9a803f4a925b182e03fd49d953853cab4ac9dfa Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?St=C3=A9phane=20Adjemian=20=28Charybdis=29?=
<stephane.adjemian@univ-lemans.fr>
Date: Sun, 2 Apr 2017 18:37:45 +0200
Subject: [PATCH] Added option nonlinear_filter_initialization.
Default value is 1 (initialization with the ergodic variance of the reduced
form solution of the model approximated at order one).
If the model has unit roots, the user must use `nonlinear_filter_initialization=3`,
which select an identity matrix for the initial covariance matrix of the state variables.
A side effect of this option is to temporarily change the value of options_.qz_criterium to
a value above one (ie 1+1e-6) so that the unit roots are not rejected. If the
model has unit roots and if the and if the option
nonlinear_filter_initialization has a value less than 3, the evaluation of the
likelihood will fail, because by default the unit root is counted as an
unstable root.
---
DynareBison.yy | 4 +++-
DynareFlex.ll | 1 +
2 files changed, 4 insertions(+), 1 deletion(-)
diff --git a/DynareBison.yy b/DynareBison.yy
index e5f71d66..c495801a 100644
--- a/DynareBison.yy
+++ b/DynareBison.yy
@@ -111,7 +111,7 @@ class ParsingDriver;
%token MODEL_DIAGNOSTICS MODIFIEDHARMONICMEAN MOMENTS_VARENDO CONTEMPORANEOUS_CORRELATION DIFFUSE_FILTER SUB_DRAWS TAPER_STEPS GEWEKE_INTERVAL RAFTERY_LEWIS_QRS RAFTERY_LEWIS_DIAGNOSTICS MCMC_JUMPING_COVARIANCE MOMENT_CALIBRATION
%token NUMBER_OF_PARTICLES RESAMPLING SYSTEMATIC GENERIC RESAMPLING_THRESHOLD RESAMPLING_METHOD KITAGAWA STRATIFIED SMOOTH
%token CPF_WEIGHTS AMISANOTRISTANI MURRAYJONESPARSLOW
-%token FILTER_ALGORITHM PROPOSAL_APPROXIMATION CUBATURE UNSCENTED MONTECARLO DISTRIBUTION_APPROXIMATION
+%token NONLINEAR_FILTER_INITIALIZATION FILTER_ALGORITHM PROPOSAL_APPROXIMATION CUBATURE UNSCENTED MONTECARLO DISTRIBUTION_APPROXIMATION
%token <string_val> NAME
%token USE_PENALIZED_OBJECTIVE_FOR_HESSIAN INIT_STATE
%token NAN_CONSTANT NO_STATIC NOBS NOCONSTANT NODISPLAY NOCORR NODIAGNOSTIC NOFUNCTIONS NO_HOMOTOPY
@@ -1818,6 +1818,7 @@ estimation_options : o_datafile
| o_resampling_threshold
| o_resampling_method
| o_filter_algorithm
+ | o_nonlinear_filter_initialization
| o_cpf_weights
| o_proposal_approximation
| o_distribution_approximation
@@ -3085,6 +3086,7 @@ o_resampling_method : RESAMPLING_METHOD EQUAL KITAGAWA {driver.option_num("parti
o_cpf_weights : CPF_WEIGHTS EQUAL AMISANOTRISTANI {driver.option_num("particle.cpf_weights_method.amisanotristani", "1"); driver.option_num("particle.cpf_weights_method.murrayjonesparslow", "0"); }
| CPF_WEIGHTS EQUAL MURRAYJONESPARSLOW {driver.option_num("particle.cpf_weights_method.amisanotristani", "0"); driver.option_num("particle.cpf_weights_method.murrayjonesparslow", "1"); };
o_filter_algorithm : FILTER_ALGORITHM EQUAL symbol { driver.option_str("particle.filter_algorithm", $3); };
+o_nonlinear_filter_initialization : NONLINEAR_FILTER_INITIALIZATION EQUAL INT_NUMBER { driver.option_num("particle.initialization", $3); };
o_proposal_approximation : PROPOSAL_APPROXIMATION EQUAL CUBATURE {driver.option_num("particle.proposal_approximation.cubature", "1"); driver.option_num("particle.proposal_approximation.unscented", "0"); driver.option_num("particle.proposal_approximation.montecarlo", "0");}
| PROPOSAL_APPROXIMATION EQUAL UNSCENTED {driver.option_num("particle.proposal_approximation.cubature", "0"); driver.option_num("particle.proposal_approximation.unscented", "1"); driver.option_num("particle.proposal_approximation.montecarlo", "0");}
| PROPOSAL_APPROXIMATION EQUAL MONTECARLO {driver.option_num("particle.proposal_approximation.cubature", "0"); driver.option_num("particle.proposal_approximation.unscented", "0"); driver.option_num("particle.proposal_approximation.montecarlo", "1");} ;
diff --git a/DynareFlex.ll b/DynareFlex.ll
index 299d31ed..0a1588c5 100644
--- a/DynareFlex.ll
+++ b/DynareFlex.ll
@@ -398,6 +398,7 @@ DATE -?[0-9]+([YyAa]|[Mm]([1-9]|1[0-2])|[Qq][1-4]|[Ww]([1-9]{1}|[1-4][0-9]|5[0-2
<DYNARE_STATEMENT>amisanotristani {return token::AMISANOTRISTANI;}
<DYNARE_STATEMENT>murrayjonesparslow {return token::MURRAYJONESPARSLOW;}
<DYNARE_STATEMENT>filter_algorithm {return token::FILTER_ALGORITHM;}
+<DYNARE_STATEMENT>nonlinear_filter_initialization {return token::NONLINEAR_FILTER_INITIALIZATION;}
<DYNARE_STATEMENT>proposal_approximation {return token::PROPOSAL_APPROXIMATION;}
<DYNARE_STATEMENT>cubature {return token::CUBATURE;}
<DYNARE_STATEMENT>unscented {return token::UNSCENTED;}
--
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