Fix trace plots with measurement errors and their correlations
Problem was introduced when transitioning to cell arraystime-shift
parent
acdca03e43
commit
f717712ed6
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@ -87,7 +87,7 @@ end
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if strcmpi(type,'MeasurementError')
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if nargin<6% Covariance matrix diagonal term
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i = nvx + strmatch(name1, M_.endo_names{estim_params_.var_endo(:,1)}, 'exact');
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i = nvx + strmatch(name1, M_.endo_names(estim_params_.var_endo(:,1)), 'exact');
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if isempty(i)
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disp(['The standard deviation of the measurement error on ' name1 ' is not an estimated parameter!'])
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return
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@ -95,7 +95,7 @@ if strcmpi(type,'MeasurementError')
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else% Covariance matrix off-diagonal term
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offset = nvx+nvn+ncx;
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try
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list_of_measurement_errors = { M_.endo_names{estim_params_.corrn(:,1)} , M_.endo_names{estim_params_.corrn(:,2)} };
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list_of_measurement_errors = [M_.endo_names(estim_params_.corrn(:,1),1) , M_.endo_names(estim_params_.corrn(:,2),1)];
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k1 = strmatch(name1,list_of_measurement_errors(:,1),'exact');
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k2 = strmatch(name2,list_of_measurement_errors(:,2),'exact');
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i = offset+intersect(k1,k2);
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@ -133,9 +133,7 @@ if ncn
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bayestopt_.p4 = [ bayestopt_.p4; estim_params_.corrn(:,10)]; %take generalized distribution into account
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bayestopt_.jscale = [ bayestopt_.jscale; estim_params_.corrn(:,11)];
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baseid = length(bayestopt_.name);
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bayestopt_.name = [bayestopt_.name; cell(ncn, 1)]; [bayestopt_.name; cellstr([repmat('corr ',ncn,1) ...
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M_.endo_names{estim_params_.corrn(:,1)} ...
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repmat(', ',ncn,1) , M_.endo_names{estim_params_.corrn(:,2)}])];
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bayestopt_.name = [bayestopt_.name; cell(ncn, 1)];;
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for i=1:ncn
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k1 = estim_params_.corrn(i,1);
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k2 = estim_params_.corrn(i,2);
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@ -61,7 +61,10 @@ stderr e_ys,inv_gamma_pdf,1.2533,0.6551;
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stderr e_pies,inv_gamma_pdf,1.88,0.9827;
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stderr dq,inv_gamma_pdf,0.001,0.0001;
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stderr de,inv_gamma_pdf,0.001,0.0001;
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stderr pie_obs,inv_gamma_pdf,0.001,0.0001;
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corr dq,de, normal_pdf,0,1;
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corr pie_obs,de, normal_pdf,0,1;
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end;
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estimation(datafile=data_ca1,first_obs=8,nobs=79,mh_nblocks=10,prefilter=1,mh_jscale=0.5,mh_replic=0,mode_check);
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estimation(datafile=data_ca1,first_obs=8,nobs=79,mh_nblocks=1,prefilter=1,mh_jscale=0.5,mh_replic=3000,mode_check);
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generate_trace_plots(1);
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