diff --git a/matlab/+occbin/IVF_core.m b/matlab/+occbin/IVF_core.m
index 1ffe0a153515810cdc992906a6b0cae5fc17b1de..b3415d3129fcb3097db0106279f07eb71b0b44be 100644
--- a/matlab/+occbin/IVF_core.m
+++ b/matlab/+occbin/IVF_core.m
@@ -1,5 +1,5 @@
function [filtered_errs, resids, Emat, stateval, error_code] = IVF_core(M_,oo_,options_,err_index,filtered_errs_init,my_obs_list,obs,init_val)
-% function [filtered_errs, resids, Emat, stateval] = IVF_core(M_,oo_,options_,err_index,filtered_errs_init,my_obs_list,obs,init_val)
+% function [filtered_errs, resids, Emat, stateval, error_code] = IVF_core(M_,oo_,options_,err_index,filtered_errs_init,my_obs_list,obs,init_val)
% Computes thre
%
% Outputs:
diff --git a/matlab/+occbin/IVF_posterior.m b/matlab/+occbin/IVF_posterior.m
index 533f5f6692f5b02e70e083426b4fbf66c347eb20..b00da8c56f4da6d932ece294df72b6d1044841b1 100644
--- a/matlab/+occbin/IVF_posterior.m
+++ b/matlab/+occbin/IVF_posterior.m
@@ -106,7 +106,13 @@ filtered_errs_init = zeros(sample_length,sum(err_index));
if info(1)
fval = Inf;
exit_flag = 0;
+ atT=NaN(size(stateval(:,DynareResults.dr.order_var)'));
+ innov=NaN(Model.exo_nbr,sample_length);
return
+else
+ atT = stateval(:,DynareResults.dr.order_var)';
+ innov = zeros(Model.exo_nbr,sample_length);
+ innov(diag(Model.Sigma_e)~=0,:)=filtered_errs';
end
nobs=size(filtered_errs,1);
@@ -184,15 +190,4 @@ end
% remember that the likelihood has already been multiplied by -1
% hence, posterior is -1 times the log of the prior
-fval = like+prior;
-atT = stateval(:,DynareResults.dr.order_var)';
-innov = zeros(Model.exo_nbr,sample_length);
-innov(diag(Model.Sigma_e)~=0,:)=filtered_errs';
-updated_variables = atT*nan;
-BayesInfo.mf = BayesInfo.smoother_var_list(BayesInfo.smoother_mf);
-
-
-initDynareOptions=DynareOptions;
-DynareOptions.nk=[]; %unset options_.nk and reset it later
-[DynareResults]=store_smoother_results(Model,DynareResults,DynareOptions,BayesInfo,dataset_,obs_info,atT,innov,[],updated_variables,DynareResults.dr.ys,zeros(length(DynareOptions.varobs_id),1));
-DynareOptions=initDynareOptions;
+fval = like+prior;
\ No newline at end of file
diff --git a/matlab/dynare_estimation_1.m b/matlab/dynare_estimation_1.m
index 44a77ede2697d5b75f57b9cab722c6f4e678b942..b22b30fee0fa2ca39877971914f4873c46f25911 100644
--- a/matlab/dynare_estimation_1.m
+++ b/matlab/dynare_estimation_1.m
@@ -175,13 +175,20 @@ if isequal(options_.mode_compute,0) && isempty(options_.mode_file) && ~options_.
if options_.order==1 && ~options_.particle.status
if options_.smoother
if options_.occbin.smoother.status && options_.occbin.smoother.inversion_filter
- [~, ~, ~, ~, ~, ~, ~, ~, ~, ~, oo_, atT, innov] = occbin.IVF_posterior(xparam1,dataset_,dataset_info,options_,M_,estim_params_,bayestopt_,prior_bounds(bayestopt_,options_.prior_trunc),oo_);
- updated_variables = atT*nan;
- measurement_error=[];
- ys = oo_.dr.ys;
- trend_coeff = zeros(length(options_.varobs_id),1);
- bayestopt_.mf = bayestopt_.smoother_var_list(bayestopt_.smoother_mf);
- [oo_]=store_smoother_results(M_,oo_,options_,bayestopt_,dataset_,dataset_info,atT,innov,measurement_error,updated_variables,ys,trend_coeff);
+ [~, info, ~, ~, ~, ~, ~, ~, ~, ~, oo_, atT, innov] = occbin.IVF_posterior(xparam1,dataset_,dataset_info,options_,M_,estim_params_,bayestopt_,prior_bounds(bayestopt_,options_.prior_trunc),oo_);
+ if ismember(info(1),[303,304,306])
+ fprintf('\nIVF: smoother did not succeed. No results will be written to oo_.\n')
+ else
+ updated_variables = atT*nan;
+ measurement_error=[];
+ ys = oo_.dr.ys;
+ trend_coeff = zeros(length(options_.varobs_id),1);
+ bayestopt_.mf = bayestopt_.smoother_var_list(bayestopt_.smoother_mf);
+ options_nk=options_.nk;
+ options_.nk=[]; %unset options_.nk and reset it later
+ [oo_]=store_smoother_results(M_,oo_,options_,bayestopt_,dataset_,dataset_info,atT,innov,measurement_error,updated_variables,ys,trend_coeff);
+ options_.nk=options_nk;
+ end
else
if options_.occbin.smoother.status
[atT,innov,measurement_error,updated_variables,ys,trend_coeff,aK,T,R,P,PK,decomp,Trend,state_uncertainty,M_,oo_,bayestopt_] = occbin.DSGE_smoother(xparam1,gend,transpose(data),data_index,missing_value,M_,oo_,options_,bayestopt_,estim_params_,dataset_,dataset_info);
@@ -590,13 +597,20 @@ if (~((any(bayestopt_.pshape > 0) && options_.mh_replic) || (any(bayestopt_.psha
|| ~options_.smoother ) && ~options_.partial_information % to be fixed
%% ML estimation, or posterior mode without Metropolis-Hastings or Metropolis without Bayesian smoothed variables
if options_.occbin.smoother.status && options_.occbin.smoother.inversion_filter
- [~, ~, ~, ~, ~, ~, ~, ~, ~, ~, oo_, atT, innov] = occbin.IVF_posterior(xparam1,dataset_,dataset_info,options_,M_,estim_params_,bayestopt_,prior_bounds(bayestopt_,options_.prior_trunc),oo_);
- updated_variables = atT*nan;
- measurement_error=[];
- ys = oo_.dr.ys;
- trend_coeff = zeros(length(options_.varobs_id),1);
- bayestopt_.mf = bayestopt_.smoother_var_list(bayestopt_.smoother_mf);
- [oo_, yf]=store_smoother_results(M_,oo_,options_,bayestopt_,dataset_,dataset_info,atT,innov,measurement_error,updated_variables,ys,trend_coeff);
+ [~, info, ~, ~, ~, ~, ~, ~, ~, ~, oo_, atT, innov] = occbin.IVF_posterior(xparam1,dataset_,dataset_info,options_,M_,estim_params_,bayestopt_,prior_bounds(bayestopt_,options_.prior_trunc),oo_);
+ if ismember(info(1),[303,304,306])
+ fprintf('\nIVF: smoother did not succeed. No results will be written to oo_.\n')
+ else
+ updated_variables = atT*nan;
+ measurement_error=[];
+ ys = oo_.dr.ys;
+ trend_coeff = zeros(length(options_.varobs_id),1);
+ bayestopt_.mf = bayestopt_.smoother_var_list(bayestopt_.smoother_mf);
+ options_nk=options_.nk;
+ options_.nk=[]; %unset options_.nk and reset it later
+ [oo_, yf]=store_smoother_results(M_,oo_,options_,bayestopt_,dataset_,dataset_info,atT,innov,measurement_error,updated_variables,ys,trend_coeff);
+ options_.nk=options_nk;
+ end
else
if options_.occbin.smoother.status
[atT,innov,measurement_error,updated_variables,ys,trend_coeff,aK,T,R,P,PK,decomp,Trend,state_uncertainty,M_,oo_,bayestopt_] = occbin.DSGE_smoother(xparam1,dataset_.nobs,transpose(dataset_.data),dataset_info.missing.aindex,dataset_info.missing.state,M_,oo_,options_,bayestopt_,estim_params_,dataset_,dataset_info);
diff --git a/matlab/evaluate_smoother.m b/matlab/evaluate_smoother.m
index fd94f8027bb5814b51397bd4e6c7ccf1f6d3460d..783976244d75cec1864b05770f0d8e7523211f3a 100644
--- a/matlab/evaluate_smoother.m
+++ b/matlab/evaluate_smoother.m
@@ -105,12 +105,17 @@ end
if options_.occbin.smoother.status
if options_.occbin.smoother.inversion_filter
- [~, ~, ~, ~, ~, ~, ~, ~, ~, ~, oo_, atT, innov] = occbin.IVF_posterior(parameters,dataset_,dataset_info,options_,M_,estim_params_,bayestopt_,prior_bounds(bayestopt_,options_.prior_trunc),oo_);
- updated_variables = atT*nan;
- measurement_error=[];
- ys = oo_.dr.ys;
- trend_coeff = zeros(length(options_.varobs_id),1);
- bayestopt_.mf = bayestopt_.smoother_var_list(bayestopt_.smoother_mf);
+ [~, info, ~, ~, ~, ~, ~, ~, ~, ~, oo_, atT, innov] = occbin.IVF_posterior(parameters,dataset_,dataset_info,options_,M_,estim_params_,bayestopt_,prior_bounds(bayestopt_,options_.prior_trunc),oo_);
+ if ismember(info(1),[303,304,306])
+ oo_.occbin.smoother.error_flag=1;
+ else
+ oo_.occbin.smoother.error_flag=0;
+ updated_variables = atT*nan;
+ measurement_error=[];
+ ys = oo_.dr.ys;
+ trend_coeff = zeros(length(options_.varobs_id),1);
+ bayestopt_.mf = bayestopt_.smoother_var_list(bayestopt_.smoother_mf);
+ end
else
[atT,innov,measurement_error,updated_variables,ys,trend_coeff,aK,T,R,P,PK,decomp,Trend,state_uncertainty,M_,oo_,bayestopt_] = ...
occbin.DSGE_smoother(parameters,dataset_.nobs,transpose(dataset_.data),dataset_info.missing.aindex,dataset_info.missing.state,M_,oo_,options_,bayestopt_,estim_params_,dataset_,dataset_info);
@@ -124,7 +129,14 @@ if ~(options_.occbin.smoother.status && options_.occbin.smoother.inversion_filte
[oo_]=store_smoother_results(M_,oo_,options_,bayestopt_,dataset_,dataset_info,atT,innov,measurement_error,updated_variables,ys,trend_coeff,aK,P,PK,decomp,Trend,state_uncertainty);
end
else
- [oo_]=store_smoother_results(M_,oo_,options_,bayestopt_,dataset_,dataset_info,atT,innov,measurement_error,updated_variables,ys,trend_coeff);
+ if ~oo_.occbin.smoother.error_flag
+ options_nk=options_.nk;
+ options_.nk=[]; %unset options_.nk and reset it later
+ [oo_]=store_smoother_results(M_,oo_,options_,bayestopt_,dataset_,dataset_info,atT,innov,measurement_error,updated_variables,ys,trend_coeff);
+ options_.nk=options_nk;
+ else
+ fprintf('\nIVF: smoother did not succeed. No results will be written to oo_.\n')
+ end
end
if nargout>4
Smoothed_variables_declaration_order_deviation_form=atT(oo_.dr.inv_order_var(bayestopt_.smoother_var_list),:);
diff --git a/matlab/perfect-foresight-models/sim1.m b/matlab/perfect-foresight-models/sim1.m
index d6382a0fbb16771a2a7ad8f9a9860378c1b2775d..f5cd589a44d797bb636790c8f7b186059233cc64 100644
--- a/matlab/perfect-foresight-models/sim1.m
+++ b/matlab/perfect-foresight-models/sim1.m
@@ -68,8 +68,9 @@ for iter = 1:options.simul.maxit
% A is the stacked Jacobian with period x equations alongs the rows and
% periods times variables (in declaration order) along the columns
if options.debug && iter==1
- row=find(all(A==0,2));
- column=find(all(A==0,1));
+ [row,col]=find(A);
+ row=setdiff(1:periods*ny,row);
+ column=setdiff(1:periods*ny,col);
if ~isempty(row) || ~isempty(column)
fprintf('The stacked Jacobian is singular. The problem derives from:\n')
if ~isempty(row)
diff --git a/tests/occbin/filter/NKM.mod b/tests/occbin/filter/NKM.mod
index cd871d250a839b3071884e5fd2f4048f2f00ab19..4eae3535ce942b03e82b87a02c4e312a4d0c1f90 100644
--- a/tests/occbin/filter/NKM.mod
+++ b/tests/occbin/filter/NKM.mod
@@ -11,10 +11,6 @@
@#define small_model = 0
@#endif
-// if ~exist('run_ivf','var')
-run_ivf=0;
-// end
-
// ----------------- Defintions -----------------------------------------//
var
c //1 Consumption
@@ -278,8 +274,6 @@ check;
varobs yg inom pi;
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
varphip,,0,inf,NORMAL_PDF,100,25;
phipi,,,,NORMAL_PDF,2,0.25;
phiy,,0,inf,NORMAL_PDF,0.5,0.25;
@@ -291,8 +285,6 @@ varobs yg inom pi;
sigi,,,,INV_GAMMA_PDF,0.002,0.002;
end;
-
-// dataloading_jme_beta(1,'sims.txt',30);
load('dataobsfile','inom')
// check if inom is at lb and remove data + associated shock
verbatim;
@@ -338,4 +330,12 @@ varobs yg inom pi;
subplot(223)
plot([oo0.SmoothedShocks.epss oo_.SmoothedShocks.epss]), title('epss')
legend('PKF','IF')
+ figure,
+ subplot(221)
+ plot([oo0.SmoothedVariables.inom oo_.SmoothedVariables.inom]), title('inom')
+ subplot(222)
+ plot([oo0.SmoothedVariables.yg oo_.SmoothedVariables.yg]), title('yg')
+ subplot(223)
+ plot([oo0.SmoothedVariables.pi oo_.SmoothedVariables.pi]), title('pi')
+ legend('PKF','IF')
occbin_write_regimes(smoother);