function random_walk_metropolis_hastings(TargetFun,ProposalFun,xparam1,vv,mh_bounds,varargin) %function random_walk_metropolis_hastings(TargetFun,ProposalFun,xparam1,vv,mh_bounds,varargin) % Random walk Metropolis-Hastings algorithm. % % INPUTS % o TargetFun [char] string specifying the name of the objective % function (posterior kernel). % o xparam1 [double] (p*1) vector of parameters to be estimated (initial values). % o vv [double] (p*p) matrix, posterior covariance matrix (at the mode). % o mh_bounds [double] (p*2) matrix defining lower and upper bounds for the parameters. % o varargin list of argument following mh_bounds % % OUTPUTS % None % % ALGORITHM % Metropolis-Hastings. % % SPECIAL REQUIREMENTS % None. % Copyright (C) 2006-2008 Dynare Team % % This file is part of Dynare. % % Dynare is free software: you can redistribute it and/or modify % it under the terms of the GNU General Public License as published by % the Free Software Foundation, either version 3 of the License, or % (at your option) any later version. % % Dynare is distributed in the hope that it will be useful, % but WITHOUT ANY WARRANTY; without even the implied warranty of % MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the % GNU General Public License for more details. % % You should have received a copy of the GNU General Public License % along with Dynare. If not, see . global M_ options_ bayestopt_ %%%% %%%% Initialization of the random walk metropolis-hastings chains. %%%% [ ix2, ilogpo2, ModelName, MhDirectoryName, fblck, fline, npar, nblck, nruns, NewFile, MAX_nruns, d ] = ... metropolis_hastings_initialization(TargetFun, xparam1, vv, mh_bounds, varargin{:}); options_.lik_algo = 1; OpenOldFile = ones(nblck,1); if strcmpi(ProposalFun,'rand_multivariate_normal') n = npar; elseif strcmpi(ProposalFun,'rand_multivariate_student') n = options_.student_degrees_of_freedom; end load([MhDirectoryName '/' ModelName '_mh_history.mat'],'record'); %%%% %%%% NOW i run the (nblck-fblck+1) metropolis-hastings chains %%%% InitSizeArray = min([repmat(MAX_nruns,nblck,1) fline+nruns-1],[],2); jscale = diag(bayestopt_.jscale); for b = fblck:nblck if (options_.load_mh_file~=0) & (fline(b)>1) & OpenOldFile(b) load(['./' MhDirectoryName '/' ModelName '_mh' int2str(NewFile(b)) ... '_blck' int2str(b) '.mat']) x2 = [x2;zeros(InitSizeArray(b)-fline(b)+1,npar)]; logpo2 = [logpo2;zeros(InitSizeArray(b)-fline(b)+1,1)]; OpenOldFile(b) = 0; else x2 = zeros(InitSizeArray(b),npar); logpo2 = zeros(InitSizeArray(b),1); end if exist('OCTAVE_VERSION') diary off; else hh = waitbar(0,['Please wait... Metropolis-Hastings (' int2str(b) '/' int2str(nblck) ')...']); set(hh,'Name','Metropolis-Hastings'); end isux = 0; jsux = 0; irun = fline(b); j = 1; while j <= nruns(b) par = feval(ProposalFun, ix2(b,:), d * jscale, n); if all( par(:) > mh_bounds(:,1) ) & all( par(:) < mh_bounds(:,2) ) logpost = - feval(TargetFun, par(:), varargin{:}); else logpost = -inf; end if (logpost > -inf) & (log(rand) < logpost-ilogpo2(b)) x2(irun,:) = par; ix2(b,:) = par; logpo2(irun) = logpost; ilogpo2(b) = logpost; isux = isux + 1; jsux = jsux + 1; else x2(irun,:) = ix2(b,:); logpo2(irun) = ilogpo2(b); end prtfrc = j/nruns(b); if exist('OCTAVE_VERSION') if mod(j, 10) == 0 printf('MH: Computing Metropolis-Hastings (chain %d/%d): %3.f%% done, acception rate: %3.f%%\r', b, nblck, 100 * prtfrc, 100 * isux / j); end else waitbar(prtfrc,hh,[ '(' int2str(b) '/' int2str(nblck) ') ' sprintf('%f done, acceptation rate %f',prtfrc,isux/j)]); end if (irun == InitSizeArray(b)) | (j == nruns(b)) % Now I save the simulations save([MhDirectoryName '/' ModelName '_mh' int2str(NewFile(b)) '_blck' int2str(b) '.mat'],'x2','logpo2'); fidlog = fopen([MhDirectoryName '/metropolis.log'],'a'); fprintf(fidlog,['\n']); fprintf(fidlog,['%% Mh' int2str(NewFile(b)) 'Blck' int2str(b) ' (' datestr(now,0) ')\n']); fprintf(fidlog,' \n'); fprintf(fidlog,[' Number of simulations.: ' int2str(length(logpo2)) '\n']); fprintf(fidlog,[' Acceptation rate......: ' num2str(jsux/length(logpo2)) '\n']); fprintf(fidlog,[' Posterior mean........:\n']); for i=1:length(x2(1,:)) fprintf(fidlog,[' params:' int2str(i) ': ' num2str(mean(x2(:,i))) '\n']); end fprintf(fidlog,[' log2po:' num2str(mean(logpo2)) '\n']); fprintf(fidlog,[' Minimum value.........:\n']);; for i=1:length(x2(1,:)) fprintf(fidlog,[' params:' int2str(i) ': ' num2str(min(x2(:,i))) '\n']); end fprintf(fidlog,[' log2po:' num2str(min(logpo2)) '\n']); fprintf(fidlog,[' Maximum value.........:\n']); for i=1:length(x2(1,:)) fprintf(fidlog,[' params:' int2str(i) ': ' num2str(max(x2(:,i))) '\n']); end fprintf(fidlog,[' log2po:' num2str(max(logpo2)) '\n']); fprintf(fidlog,' \n'); fclose(fidlog); jsux = 0; if j == nruns(b) % I record the last draw... record.LastParameters(b,:) = x2(end,:); record.LastLogLiK(b) = logpo2(end); end % size of next file in chain b InitSizeArray(b) = min(nruns(b)-j,MAX_nruns); % initialization of next file if necessary if InitSizeArray(b) x2 = zeros(InitSizeArray(b),npar); logpo2 = zeros(InitSizeArray(b),1); NewFile(b) = NewFile(b) + 1; irun = 0; end end j=j+1; irun = irun + 1; end% End of the simulations for one mh-block. record.AcceptationRates(b) = isux/j; if exist('OCTAVE_VERSION') printf('\n'); diary on; else close(hh); end end% End of the loop over the mh-blocks. record.Seeds.Normal = randn('state'); record.Seeds.Unifor = rand('state'); save([MhDirectoryName '/' ModelName '_mh_history.mat'],'record'); disp(['MH: Number of mh files : ' int2str(NewFile(1)) ' per block.']) disp(['MH: Total number of generated files : ' int2str(NewFile(1)*nblck) '.']) disp(['MH: Total number of iterations : ' int2str((NewFile(1)-1)*MAX_nruns+irun-1) '.']) disp('MH: average acceptation rate per chain : ') disp(record.AcceptationRates); disp(' ')