381 lines
17 KiB
Matlab
381 lines
17 KiB
Matlab
function oo_ = GetPosteriorParametersStatistics(estim_params_, M_, options_, bayestopt_, oo_, pnames)
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% This function prints and saves posterior estimates after the mcmc
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% (+updates of oo_ & TeX output).
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%
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% INPUTS
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% estim_params_ [structure]
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% M_ [structure]
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% options_ [structure]
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% bayestopt_ [structure]
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% oo_ [structure]
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% pnames [cell] cell of strings, names of the prior shapes available
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%
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% OUTPUTS
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% oo_ [structure]
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%
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% SPECIAL REQUIREMENTS
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% None.
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% Copyright © 2006-2018 Dynare Team
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%
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% This file is part of Dynare.
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%
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% Dynare is free software: you can redistribute it and/or modify
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% it under the terms of the GNU General Public License as published by
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% the Free Software Foundation, either version 3 of the License, or
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% (at your option) any later version.
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%
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% Dynare is distributed in the hope that it will be useful,
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% but WITHOUT ANY WARRANTY; without even the implied warranty of
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% MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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% GNU General Public License for more details.
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%
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% You should have received a copy of the GNU General Public License
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% along with Dynare. If not, see <https://www.gnu.org/licenses/>.
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%if ~options_.mh_replic && options_.load_mh_file
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% load([M_.fname '_results.mat'],'oo_');
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%end
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TeX = options_.TeX;
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nblck = options_.mh_nblck;
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nvx = estim_params_.nvx;
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nvn = estim_params_.nvn;
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ncx = estim_params_.ncx;
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ncn = estim_params_.ncn;
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np = estim_params_.np ;
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nx = nvx+nvn+ncx+ncn+np;
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MetropolisFolder = CheckPath('metropolis',M_.dname);
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OutputFolder = CheckPath('Output',M_.dname);
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FileName = M_.fname;
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load_last_mh_history_file(MetropolisFolder,FileName);
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FirstMhFile = record.KeepedDraws.FirstMhFile;
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FirstLine = record.KeepedDraws.FirstLine;
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TotalNumberOfMhFiles = sum(record.MhDraws(:,2));
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TotalNumberOfMhDraws = sum(record.MhDraws(:,1));
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FirstMhFile = record.KeepedDraws.FirstMhFile;
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NumberOfDraws = TotalNumberOfMhDraws-floor(options_.mh_drop*TotalNumberOfMhDraws);
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clear record;
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header_width = row_header_width(M_, estim_params_, bayestopt_);
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hpd_interval=[num2str(options_.mh_conf_sig*100), '% HPD interval'];
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tit2 = sprintf('%-*s %12s %12s %23s %8s %12s\n',header_width,' ','prior mean','post. mean',hpd_interval,'prior','pstdev');
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pformat = '%-*s %12.3f % 12.4f %11.4f %11.4f %8s %12.4f';
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skipline(2)
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disp('ESTIMATION RESULTS')
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skipline()
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try
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disp(sprintf('Log data density is %f.', oo_.MarginalDensity.ModifiedHarmonicMean))
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catch
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[marginal,oo_] = marginal_density(M_, options_, estim_params_, oo_, bayestopt_);
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disp(sprintf('Log data density is %f.', oo_.MarginalDensity.ModifiedHarmonicMean))
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end
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num_draws=NumberOfDraws*options_.mh_nblck;
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hpd_draws = round((1-options_.mh_conf_sig)*num_draws);
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if hpd_draws<2
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fprintf('posterior_moments: There are not enough draws computes to compute HPD Intervals. Skipping their computation.\n')
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end
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if num_draws<9
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fprintf('posterior_moments: There are not enough draws computes to compute deciles. Skipping their computation.\n')
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end
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if np
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type = 'parameters';
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if TeX
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fid = TeXBegin(OutputFolder, M_.fname, 1, type);
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end
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skipline()
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disp(type)
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disp(tit2)
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ip = nvx+nvn+ncx+ncn+1;
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for i=1:np
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if options_.mh_replic || (options_.load_mh_file && ~options_.load_results_after_load_mh)
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Draws = GetAllPosteriorDraws(ip, FirstMhFile, FirstLine, TotalNumberOfMhFiles, NumberOfDraws);
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[post_mean, post_median, post_var, hpd_interval, post_deciles, density] = posterior_moments(Draws, 1, options_.mh_conf_sig);
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name = bayestopt_.name{ip};
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oo_ = Filloo(oo_, name, type, post_mean, hpd_interval, post_median, post_var, post_deciles, density);
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else
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try
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name = bayestopt_.name{ip};
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[post_mean, hpd_interval, post_var] = Extractoo(oo_, name, type);
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catch
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Draws = GetAllPosteriorDraws(ip, FirstMhFile, FirstLine, TotalNumberOfMhFiles, NumberOfDraws);
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[post_mean, post_median, post_var, hpd_interval, post_deciles, density] = posterior_moments(Draws, 1, options_.mh_conf_sig);
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name = bayestopt_.name{ip};
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oo_ = Filloo(oo_, name, type, post_mean, hpd_interval, post_median, post_var, post_deciles, density);
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end
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end
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disp(sprintf(pformat, header_width, name, bayestopt_.p1(ip),...
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post_mean, ...
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hpd_interval, ...
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pnames{bayestopt_.pshape(ip)+1}, ...
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bayestopt_.p2(ip)));
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if TeX
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k = estim_params_.param_vals(i,1);
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name = M_.param_names_tex{k};
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TeXCore(fid, name, pnames{bayestopt_.pshape(ip)+1}, bayestopt_.p1(ip), bayestopt_.p2(ip), post_mean, sqrt(post_var), hpd_interval);
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end
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ip = ip+1;
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end
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if TeX
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TeXEnd(fid, 1, type);
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end
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end
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if nvx
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type = 'shocks_std';
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if TeX
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fid = TeXBegin(OutputFolder, FileName,2, 'standard deviation of structural shocks');
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end
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ip = 1;
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skipline()
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disp('standard deviation of shocks')
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disp(tit2)
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for i=1:nvx
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if options_.mh_replic || (options_.load_mh_file && ~options_.load_results_after_load_mh)
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Draws = GetAllPosteriorDraws(ip, FirstMhFile, FirstLine, TotalNumberOfMhFiles, NumberOfDraws);
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[post_mean, post_median, post_var, hpd_interval, post_deciles, density] = posterior_moments(Draws, 1, options_.mh_conf_sig);
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k = estim_params_.var_exo(i,1);
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name = M_.exo_names{k};
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oo_ = Filloo(oo_, name, type, post_mean, hpd_interval, post_median, post_var, post_deciles, density);
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M_.Sigma_e(k,k) = post_mean*post_mean;
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else
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try
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k = estim_params_.var_exo(i,1);
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name = M_.exo_names{k};
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[post_mean, hpd_interval, post_var] = Extractoo(oo_, name, type);
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catch
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Draws = GetAllPosteriorDraws(ip, FirstMhFile, FirstLine, TotalNumberOfMhFiles, NumberOfDraws);
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[post_mean, post_median, post_var, hpd_interval, post_deciles, density] = ...
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posterior_moments(Draws, 1, options_.mh_conf_sig);
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k = estim_params_.var_exo(i,1);
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name = M_.exo_names{k};
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oo_ = Filloo(oo_, name, type, post_mean, hpd_interval, post_median, post_var, post_deciles, density);
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M_.Sigma_e(k,k) = post_mean*post_mean;
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end
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end
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disp(sprintf(pformat,header_width,name, bayestopt_.p1(ip), post_mean, hpd_interval, pnames{bayestopt_.pshape(ip)+1}, bayestopt_.p2(ip)));
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if TeX
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name = M_.exo_names_tex{k};
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TeXCore(fid,name, pnames{bayestopt_.pshape(ip)+1}, bayestopt_.p1(ip), bayestopt_.p2(ip), post_mean, sqrt(post_var), hpd_interval);
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end
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ip = ip+1;
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end
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if TeX
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TeXEnd(fid, 2, 'standard deviation of structural shocks');
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end
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end
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if nvn
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type = 'measurement_errors_std';
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if TeX
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fid = TeXBegin(OutputFolder, FileName, 3, 'standard deviation of measurement errors');
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end
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skipline()
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disp('standard deviation of measurement errors')
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disp(tit2)
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ip = nvx+1;
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for i=1:nvn
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if options_.mh_replic || (options_.load_mh_file && ~options_.load_results_after_load_mh)
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Draws = GetAllPosteriorDraws(ip, FirstMhFile, FirstLine, TotalNumberOfMhFiles, NumberOfDraws);
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[post_mean, post_median, post_var, hpd_interval, post_deciles, density] = posterior_moments(Draws, 1, options_.mh_conf_sig);
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name = options_.varobs{estim_params_.nvn_observable_correspondence(i,1)};
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oo_ = Filloo(oo_, name, type, post_mean, hpd_interval, post_median, post_var, post_deciles, density);
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else
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try
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name = options_.varobs{estim_params_.nvn_observable_correspondence(i,1)};
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[post_mean,hpd_interval,post_var] = Extractoo(oo_,name,type);
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catch
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Draws = GetAllPosteriorDraws(ip,FirstMhFile,FirstLine,TotalNumberOfMhFiles,NumberOfDraws);
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[post_mean, post_median, post_var, hpd_interval, post_deciles, density] = posterior_moments(Draws,1,options_.mh_conf_sig);
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name = options_.varobs{estim_params_.nvn_observable_correspondence(i,1)};
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oo_ = Filloo(oo_,name,type,post_mean,hpd_interval,post_median,post_var,post_deciles,density);
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end
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end
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disp(sprintf(pformat, header_width, name,bayestopt_.p1(ip), post_mean, hpd_interval, pnames{bayestopt_.pshape(ip)+1}, bayestopt_.p2(ip)));
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if TeX
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k = estim_params_.var_endo(i,1);
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name = M_.endo_names_tex{k};
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TeXCore(fid, name, pnames{bayestopt_.pshape(ip)+1}, bayestopt_.p1(ip), bayestopt_.p2(ip), post_mean, sqrt(post_var), hpd_interval);
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end
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ip = ip+1;
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end
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if TeX
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TeXEnd(fid, 3, 'standard deviation of measurement errors');
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end
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end
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if ncx
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type = 'shocks_corr';
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if TeX
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fid = TeXBegin(OutputFolder,FileName,4,'correlation of structural shocks');
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end
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skipline()
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disp('correlation of shocks')
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disp(tit2)
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ip = nvx+nvn+1;
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for i=1:ncx
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if options_.mh_replic || (options_.load_mh_file && ~options_.load_results_after_load_mh)
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Draws = GetAllPosteriorDraws(ip, FirstMhFile, FirstLine, TotalNumberOfMhFiles, NumberOfDraws);
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[post_mean, post_median, post_var, hpd_interval, post_deciles, density] = posterior_moments(Draws,1,options_.mh_conf_sig);
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k1 = estim_params_.corrx(i,1);
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k2 = estim_params_.corrx(i,2);
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name = sprintf('%s,%s', M_.exo_names{k1}, M_.exo_names{k2});
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NAME = sprintf('%s_%s', M_.exo_names{k1}, M_.exo_names{k2});
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oo_ = Filloo(oo_, NAME, type, post_mean, hpd_interval, post_median, post_var, post_deciles, density);
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M_.Sigma_e(k1,k2) = post_mean*sqrt(M_.Sigma_e(k1,k1)*M_.Sigma_e(k2,k2));
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M_.Sigma_e(k2,k1) = M_.Sigma_e(k1,k2);
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else
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try
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k1 = estim_params_.corrx(i,1);
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k2 = estim_params_.corrx(i,2);
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name = sprintf('%s,%s', M_.exo_names{k1}, M_.exo_names{k2});
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NAME = sprintf('%s_%s', M_.exo_names{k1}, M_.exo_names{k2});
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[post_mean,hpd_interval,post_var] = Extractoo(oo_, NAME, type);
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catch
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Draws = GetAllPosteriorDraws(ip, FirstMhFile, FirstLine, TotalNumberOfMhFiles, NumberOfDraws);
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[post_mean, post_median, post_var, hpd_interval, post_deciles, density] = posterior_moments(Draws, 1, options_.mh_conf_sig);
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k1 = estim_params_.corrx(i,1);
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k2 = estim_params_.corrx(i,2);
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name = sprintf('%s,%s', M_.exo_names{k1}, M_.exo_names{k2});
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NAME = sprintf('%s_%s', M_.exo_names{k1}, M_.exo_names{k2});
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oo_ = Filloo(oo_, NAME, type, post_mean, hpd_interval, post_median, post_var, post_deciles, density);
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M_.Sigma_e(k1,k2) = post_mean*sqrt(M_.Sigma_e(k1,k1)*M_.Sigma_e(k2,k2));
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M_.Sigma_e(k2,k1) = M_.Sigma_e(k1,k2);
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end
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end
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disp(sprintf(pformat, header_width,name, bayestopt_.p1(ip), post_mean, hpd_interval, pnames{bayestopt_.pshape(ip)+1}, bayestopt_.p2(ip)));
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if TeX
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name = sprintf('(%s,%s)', M_.exo_names_tex{k1}, M_.exo_names_tex{k2});
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TeXCore(fid, name, pnames{bayestopt_.pshape(ip)+1}, bayestopt_.p1(ip), bayestopt_.p2(ip), post_mean, sqrt(post_var), hpd_interval);
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end
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ip = ip+1;
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end
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if TeX
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TeXEnd(fid, 4, 'correlation of structural shocks');
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end
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end
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if ncn
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type = 'measurement_errors_corr';
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if TeX
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fid = TeXBegin(OutputFolder, FileName, 5, 'correlation of measurement errors');
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end
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skipline()
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disp('correlation of measurement errors')
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disp(tit2)
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ip = nvx+nvn+ncx+1;
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for i=1:ncn
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if options_.mh_replic || (options_.load_mh_file && ~options_.load_results_after_load_mh)
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Draws = GetAllPosteriorDraws(ip,FirstMhFile,FirstLine,TotalNumberOfMhFiles,NumberOfDraws);
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[post_mean, post_median, post_var, hpd_interval, post_deciles, density] = posterior_moments(Draws, 1, options_.mh_conf_sig);
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k1 = estim_params_.corrn(i,1);
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k2 = estim_params_.corrn(i,2);
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name = sprintf('%s,%s', M_.endo_names{k1}, M_.endo_names{k2});
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NAME = sprintf('%s_%s', M_.endo_names{k1}, M_.endo_names{k2});
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oo_ = Filloo(oo_, NAME, type, post_mean, hpd_interval, post_median, post_var, post_deciles,density);
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else
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try
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k1 = estim_params_.corrn(i,1);
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k2 = estim_params_.corrn(i,2);
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name = sprintf('%s,%s', M_.endo_names{k1}, M_.endo_names{k2});
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NAME = sprintf('%s_%s', M_.endo_names{k1}, M_.endo_names{k2});
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[post_mean,hpd_interval,post_var] = Extractoo(oo_, NAME, type);
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catch
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Draws = GetAllPosteriorDraws(ip, FirstMhFile, FirstLine, TotalNumberOfMhFiles, NumberOfDraws);
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[post_mean, post_median, post_var, hpd_interval, post_deciles, density] = posterior_moments(Draws, 1, options_.mh_conf_sig);
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k1 = estim_params_.corrn(i,1);
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k2 = estim_params_.corrn(i,2);
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name = sprintf('%s,%s', M_.endo_names{k1}, M_.endo_names{k2});
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NAME = sprintf('%s_%s', M_.endo_names{k1}, M_.endo_names{k2});
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oo_ = Filloo(oo_, NAME, type, post_mean, hpd_interval, post_median, post_var, post_deciles, density);
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end
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end
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disp(sprintf(pformat, header_width, name, bayestopt_.p1(ip), post_mean, hpd_interval, pnames{bayestopt_.pshape(ip)+1}, bayestopt_.p2(ip)));
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if TeX
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name = sprintf('(%s,%s)', M_.endo_names_tex{k1}, M_.endo_names_tex{k2});
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TeXCore(fid, name, pnames{bayestopt_.pshape(ip)+1}, bayestopt_.p1(ip), bayestopt_.p2(ip), post_mean, sqrt(post_var), hpd_interval);
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end
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ip = ip+1;
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end
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if TeX
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TeXEnd(fid, 5, 'correlation of measurement errors');
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end
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end
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%
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%% subfunctions:
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%
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function fid = TeXBegin(directory, fname, fnum, title)
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TeXfile = [directory '/' fname '_Posterior_Mean_' int2str(fnum) '.tex'];
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fidTeX = fopen(TeXfile,'w');
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fprintf(fidTeX, '%% TeX-table generated by Dynare.\n');
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fprintf(fidTeX, ['%% RESULTS FROM METROPOLIS HASTINGS (' title ')\n']);
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fprintf(fidTeX, ['%% ' datestr(now, 0)]);
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fprintf(fidTeX, ' \n');
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fprintf(fidTeX, ' \n');
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fprintf(fidTeX, '\\begin{center}\n');
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fprintf(fidTeX, '\\begin{longtable}{llcccccc} \n');
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fprintf(fidTeX, ['\\caption{Results from Metropolis-Hastings (' title ')}\n ']);
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fprintf(fidTeX, ['\\label{Table:MHPosterior:' int2str(fnum) '}\\\\\n']);
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fprintf(fidTeX, '\\toprule \n');
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fprintf(fidTeX, ' & \\multicolumn{3}{c}{Prior} & \\multicolumn{4}{c}{Posterior} \\\\\n');
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fprintf(fidTeX, ' \\cmidrule(r{.75em}){2-4} \\cmidrule(r{.75em}){5-8}\n');
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fprintf(fidTeX, ' & Dist. & Mean & Stdev. & Mean & Stdev. & HPD inf & HPD sup\\\\\n');
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fprintf(fidTeX, '\\midrule \\endfirsthead \n');
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fprintf(fidTeX, ['\\caption{(continued)}\\\\']);
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fprintf(fidTeX, '\\toprule \n');
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fprintf(fidTeX, ' & \\multicolumn{3}{c}{Prior} & \\multicolumn{4}{c}{Posterior} \\\\\n');
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fprintf(fidTeX, ' \\cmidrule(r{.75em}){2-4} \\cmidrule(r{.75em}){5-8}\n');
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fprintf(fidTeX, ' & Dist. & Mean & Stdev. & Mean & Stdev. & HPD inf & HPD sup\\\\\n');
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fprintf(fidTeX, '\\midrule \\endhead \n');
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fprintf(fidTeX, '\\bottomrule \\multicolumn{8}{r}{(Continued on next page)} \\endfoot \n');
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fprintf(fidTeX, '\\bottomrule \\endlastfoot \n');
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fid = fidTeX;
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function TeXCore(fid, name, shape, priormean, priorstd, postmean, poststd, hpd)
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fprintf(fid,['$%s$ & %s & %7.3f & %6.4f & %7.3f& %6.4f & %7.4f & %7.4f \\\\ \n'],...
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name, ...
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shape, ...
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priormean, ...
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priorstd, ...
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postmean, ...
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poststd, ...
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hpd(1), ...
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hpd(2));
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function TeXEnd(fid, fnum, title)
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fprintf(fid, '\\end{longtable}\n ');
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fprintf(fid, '\\end{center}\n');
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fprintf(fid, '%% End of TeX file.\n');
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fclose(fid);
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function oo = Filloo(oo, name, type, postmean, hpdinterval, postmedian, postvar, postdecile, density)
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oo.posterior_mean.(type).(name) = postmean;
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oo.posterior_hpdinf.(type).(name) = hpdinterval(1);
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oo.posterior_hpdsup.(type).(name) = hpdinterval(2);
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oo.posterior_median.(type).(name) = postmedian;
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oo.posterior_variance.(type).(name) = postvar;
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oo.posterior_std.(type).(name) = sqrt(postvar);
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oo.posterior_deciles.(type).(name) = postdecile;
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oo.posterior_density.(type).(name) = density;
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|
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function [post_mean,hpd_interval,post_var] = Extractoo(oo, name, type)
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hpd_interval = zeros(2,1);
|
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post_mean = oo.posterior_mean.(type).(name);
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hpd_interval(1) = oo.posterior_hpdinf.(type).(name);
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|
hpd_interval(2) = oo.posterior_hpdsup.(type).(name);
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post_var = oo.posterior_variance.(type).(name); |