dynare/matlab/PosteriorIRF.m

function PosteriorIRF(type)
% Builds posterior IRFs after the MH algorithm. 
% 
% INPUTS 
%   o type       [char]     string specifying the joint density of the
%   deep parameters ('prior','posterior'). 
%  
% OUTPUTS 
%   None (oo_ and plots).
%
%
% ALGORITHM
%   None.       
%
% SPECIAL REQUIREMENTS
%   None.
%  
%  
% part of DYNARE, copyright S. Adjemian, M. Juillard (2006)
% Gnu Public License.
global options_ estim_params_ oo_ M_ bayestopt_
if isempty(options_.irf) | ~options_.irf 
    options_.irf = 40;
end
nvx  = estim_params_.nvx;
nvn  = estim_params_.nvn;
ncx  = estim_params_.ncx;
ncn  = estim_params_.ncn;
np   = estim_params_.np ;
npar = nvx+nvn+ncx+ncn+np;
offset = npar-np;
nvobs = size(options_.varobs,1);
gend = options_.nobs;
%
MaxNumberOfPlotPerFigure = 9;% The square root must be an integer!
nn = sqrt(MaxNumberOfPlotPerFigure);
DirectoryName = CheckPath('Output');
if strcmpi(type,'posterior')
  MhDirectoryName = CheckPath('metropolis');
elseif strcmpi(type,'gsa')
  MhDirectoryName = CheckPath('GSA');
else
  MhDirectoryName = CheckPath('prior');
end
MAX_nirfs_dsge = ceil(options_.MaxNumberOfBytes/(options_.irf*length(oo_.steady_state)*M_.exo_nbr)/8)+50;
MAX_nruns = ceil(options_.MaxNumberOfBytes/(npar+2)/8);
if ~isempty(strmatch('dsge_prior_weight',M_.param_names))
    MAX_nirfs_dsgevar = ceil(options_.MaxNumberOfBytes/(options_.irf*nvobs*M_.exo_nbr)/8)+50;
else
    MAX_nirfs_dsgevar = 0;
end
if strcmpi(type,'posterior')
  load([ MhDirectoryName '/'  M_.fname '_mh_history'])
  TotalNumberOfMhDraws = sum(record.MhDraws(:,1));
  NumberOfDraws = TotalNumberOfMhDraws-floor(options_.mh_drop*TotalNumberOfMhDraws);
elseif strcmpi(type,'gsa')
  load([ MhDirectoryName '/'  M_.fname '_prior'],'lpmat0','lpmat','istable')
  x=[lpmat0(istable,:) lpmat(istable,:)];
  clear lpmat istable
  NumberOfDraws=size(x,1);
  B=NumberOfDraws; options_.B = B;
else% type = 'prior'
  NumberOfDraws = 500;
end
if ~strcmpi(type,'gsa')
  B = min([round(.5*NumberOfDraws),500]); options_.B = B;
end
try delete([MhDirectoryName '/' M_.fname '_irf_dsge*.mat'])
catch disp('No _IRFs (dsge) files to be deleted!')
end
try delete([MhDirectoryName '/' M_.fname '_irf_bvardsge*.mat'])
catch disp('No _IRFs (bvar-dsge) files to be deleted!')
end
irun = 0;
IRUN = 0;
irun2 = 0;
NumberOfIRFfiles_dsge = 1;
NumberOfIRFfiles_dsgevar = 1;
ifil2 = 1;
if strcmpi(type,'posterior')
  h = waitbar(0,'Bayesian (posterior) IRFs...');
elseif strcmpi(type,'gsa')
  h = waitbar(0,'GSA (prior) IRFs...');
else
  h = waitbar(0,'Bayesian (prior) IRFs...');
end
if B <= MAX_nruns
  stock_param = zeros(B, npar);
else
  stock_param = zeros(MAX_nruns, npar);
end
if B >= MAX_nirfs_dsge
  stock_irf_dsge = zeros(options_.irf,M_.endo_nbr,M_.exo_nbr,MAX_nirfs_dsge);
else
  stock_irf_dsge = zeros(options_.irf,M_.endo_nbr,M_.exo_nbr,B);
end
if MAX_nirfs_dsgevar
    if B >= MAX_nirfs_dsgevar
        stock_irf_bvardsge = zeros(options_.irf,nvobs,M_.exo_nbr,MAX_nirfs_dsgevar);
    else
        stock_irf_bvardsge = zeros(options_.irf,nvobs,M_.exo_nbr,B);
    end
    [mYY,mXY,mYX,mXX,Ydata,Xdata] = ...
        var_sample_moments(options_.first_obs,options_.first_obs+options_.nobs-1,options_.varlag,-1);
    NumberOfLags = options_.varlag;
    NumberOfLagsTimesNvobs = NumberOfLags*nvobs;
    COMP_draw = diag(ones(nvobs*(NumberOfLags-1),1),-nvobs);
end
for b=1:B
  irun = irun+1;
  irun2 = irun2+1;
  if ~strcmpi(type,'gsa')
    deep = GetOneDraw(type);
  else
    deep = x(b,:);
  end
  stock_param(irun2,:) = deep;  
  set_parameters(deep);
  dr = resol(oo_.steady_state,0);
  SS(M_.exo_names_orig_ord,M_.exo_names_orig_ord) = M_.Sigma_e+1e-14*eye(M_.exo_nbr);
  SS = transpose(chol(SS));
  for i = 1:M_.exo_nbr
    if SS(i,i) > 1e-13
      y=irf(dr,SS(M_.exo_names_orig_ord,i), options_.irf, options_.drop,options_.replic,options_.order);
      if options_.relative_irf
        y = 100*y/cs(i,i);
      end
      for j = 1:M_.endo_nbr
        if max(y(j,:)) - min(y(j,:)) > 1e-10 
          stock_irf_dsge(:,j,i,irun) = transpose(y(j,:));
        end
      end
    end
  end
  if MAX_nirfs_dsgevar
      IRUN = IRUN+1;
      tmp_dsgevar = zeros(options_.irf,nvobs*M_.exo_nbr);
      [fval,cost_flag,ys,trend_coeff,info,PHI,SIGMAu,iXX] =  DsgeVarLikelihood(deep',gend);
      dsge_prior_weight = M_.params(strmatch('dsge_prior_weight',M_.param_names));
      DSGE_PRIOR_WEIGHT = floor(gend*(1+dsge_prior_weight));
      tmp1 = SIGMAu*gend*(dsge_prior_weight+1);
      val  = 1;
      tmp1 = chol(inv(tmp1))'; 
      while val;
          % draw from the marginal posterior of sig
          tmp2 = tmp1*randn(nvobs,DSGE_PRIOR_WEIGHT-NumberOfLagsTimesNvobs);
          SIGMAu_draw = inv(tmp2*tmp2');
          % draw from the conditional posterior of PHI
          VARvecPHI = kron(SIGMAu_draw,iXX);
          PHI_draw  = PHI(:) + chol(VARvecPHI)'*randn(nvobs*NumberOfLagsTimesNvobs,1);
          COMP_draw(1:nvobs,:) = reshape(PHI_draw,NumberOfLagsTimesNvobs,nvobs)';
          % Check for stationarity
          tests = find(abs(eig(COMP_draw))>0.9999999999);
          if isempty(tests)
	      val=0;
          end
      end
      % Get rotation
      if dsge_prior_weight > 0
          Atheta(oo_.dr.order_var,M_.exo_names_orig_ord) = oo_.dr.ghu*sqrt(M_.Sigma_e);
          A0 = Atheta(bayestopt_.mfys,:);
          [OMEGAstar,SIGMAtr] = qr2(A0');
      end
      SIGMAu_chol = chol(SIGMAu_draw)';
      SIGMAtrOMEGA = SIGMAu_chol*OMEGAstar';
      PHIpower = eye(NumberOfLagsTimesNvobs);
      irfs = zeros (options_.irf,nvobs*M_.exo_nbr);
      tmp3 = PHIpower(1:nvobs,1:nvobs)*SIGMAtrOMEGA;
      irfs(1,:) = tmp3(:)';
      for t = 2:options_.irf
          PHIpower = COMP_draw*PHIpower;
          tmp3 = PHIpower(1:nvobs,1:nvobs)*SIGMAtrOMEGA;
          irfs(t,:)  = tmp3(:)';
      end            
      for j = 1:(nvobs*M_.exo_nbr)
          if max(irfs(:,j)) - min(irfs(:,j)) > 1e-10 
	      tmp_dsgevar(:,j) = (irfs(:,j));
          end
      end
      if IRUN < MAX_nirfs_dsgevar
          stock_irf_bvardsge(:,:,:,IRUN) = reshape(tmp_dsgevar,options_.irf,nvobs,M_.exo_nbr);
      else
          stock_irf_bvardsge(:,:,:,IRUN) = reshape(tmp_dsgevar,options_.irf,nvobs,M_.exo_nbr);
          instr = [MhDirectoryName '/' M_.fname '_irf_bvardsge' int2str(NumberOfIRFfiles_dsgevar) ' stock_irf_bvardsge;'];,
          eval(['save ' instr]);
          NumberOfIRFfiles_dsgevar = NumberOfIRFfiles_dsgevar+1; 
          IRUN =0;
          stock_irf_dsgevar = zeros(options_.irf,nvobs,M_.exo_nbr,MAX_nirfs_dsgevar);
      end
  end
  if irun == MAX_nirfs_dsge | irun == B | b == B
    if b == B
      stock_irf_dsge = stock_irf_dsge(:,:,:,1:irun);
      if MAX_nirfs_dsgevar & (b == B | IRUN == B)
          stock_irf_bvardsge = stock_irf_bvardsge(:,:,:,1:IRUN);
          instr = [MhDirectoryName '/' M_.fname '_irf_bvardsge' int2str(NumberOfIRFfiles_dsgevar) ' stock_irf_bvardsge;'];,
          eval(['save ' instr]);
          NumberOfIRFfiles_dsgevar = NumberOfIRFfiles_dsgevar+1;
          irun = 0;
      end
    end
    save([MhDirectoryName '/' M_.fname '_irf_dsge' int2str(NumberOfIRFfiles_dsge)],'stock_irf_dsge');
    NumberOfIRFfiles_dsge = NumberOfIRFfiles_dsge+1;
    irun = 0;
  end
  if irun2 == MAX_nruns | b == B
    if b == B
      stock_param = stock_param(1:irun2,:);
    end
    stock = stock_param;
    save([MhDirectoryName '/' M_.fname '_param_irf' int2str(ifil2)],'stock');
    ifil2 = ifil2 + 1;
    irun2 = 0;
  end
  waitbar(b/B,h);
end
NumberOfIRFfiles_dsge = NumberOfIRFfiles_dsge-1;
NumberOfIRFfiles_dsgevar = NumberOfIRFfiles_dsgevar-1;

ifil2 = ifil2-1;
close(h);

ReshapeMatFiles('irf_dsge')
if MAX_nirfs_dsgevar
    ReshapeMatFiles('irf_bvardsge')
end

if strcmpi(type,'gsa')
  return
end  


varlist = options_.varlist;

if isempty(varlist)
  if MAX_nirfs_dsgevar
      varlist = options_.varobs;
      nvar = size(varlist,1);
      SelecVariables = [];
      for i=1:nvar
          if ~isempty(strmatch(varlist(i,:),M_.endo_names,'exact'))
              SelecVariables = [SelecVariables;strmatch(varlist(i,:),M_.endo_names,'exact')];
          end
      end
  else
      varlist = M_.endo_names;
      SelecVariables = transpose(1:M_.endo_nbr);
      nvar = M_.endo_nbr;
  end
else
  nvar = size(varlist,1);
  SelecVariables = [];
  for i=1:nvar
    if ~isempty(strmatch(varlist(i,:),M_.endo_names,'exact'))
      SelecVariables = [SelecVariables;strmatch(varlist(i,:),M_.endo_names,'exact')];
    end
  end
  if MAX_nirfs_dsgevar% Here I test if declared variables are observed variables.
      SelecVariables = [];
      varlistbis = [];
      for i=1:nvar
          if ~isempty(strmatch(varlist(i,:),options_.varobs,'exact'))
              SelecVariables = [SelecVariables;strmatch(varlist(i,:),M_.endo_names,'exact')];
              varlistbis = strvcat(varlistbis,varlist(i,:));
          else
              disp(' ')
              disp(['Warning :: ' varlist(i,:) 'is not an observed variable!'])
              disp(['This variable will not be considered for the IRFs.'])
              disp(' ')
          end
      end
      varlist = varlistbis;
  end 
end


MeanIRF = zeros(options_.irf,nvar,M_.exo_nbr);
MedianIRF = zeros(options_.irf,nvar,M_.exo_nbr);
VarIRF = zeros(options_.irf,nvar,M_.exo_nbr);
DistribIRF = zeros(options_.irf,9,nvar,M_.exo_nbr);
HPDIRF = zeros(options_.irf,2,nvar,M_.exo_nbr);

if options_.TeX
  varlist_TeX = [];
  for i=1:nvar
    varlist_TeX = strvcat(varlist_TeX,M_.endo_names_tex(SelecVariables(i),:));
  end
end

fprintf('MH: Posterior (dsge) IRFs...\n');
tit(M_.exo_names_orig_ord,:) = M_.exo_names;
kdx = 0;
for file = 1:NumberOfIRFfiles_dsge
  load([MhDirectoryName '/' M_.fname '_IRF_DSGEs' int2str(file)]);
  for i = 1:M_.exo_nbr
    for j = 1:nvar
      for k = 1:size(STOCK_IRF_DSGE,1)
        kk = k+kdx;
        [MeanIRF(kk,j,i),MedianIRF(kk,j,i),VarIRF(kk,j,i),HPDIRF(kk,:,j,i),DistribIRF(kk,:,j,i)] = ...
          posterior_moments(squeeze(STOCK_IRF_DSGE(k,SelecVariables(j),i,:)),0);
      end
    end
  end
  kdx = kdx + size(STOCK_IRF_DSGE,1);
end
clear STOCK_IRF_DSGE;

for i = 1:M_.exo_nbr
  for j = 1:nvar
    name = [deblank(M_.endo_names(SelecVariables(j),:)) '_' deblank(tit(i,:))];
    eval(['oo_.PosteriorIRF.dsge.Mean.' name ' = MeanIRF(:,j,i);']);
    eval(['oo_.PosteriorIRF.dsge.Median.' name ' = MedianIRF(:,j,i);']);
    eval(['oo_.PosteriorIRF.dsge.Var.' name ' = VarIRF(:,j,i);']);
    eval(['oo_.PosteriorIRF.dsge.Distribution.' name ' = DistribIRF(:,:,j,i);']);
    eval(['oo_.PosteriorIRF.dsge.HPDinf.' name ' = HPDIRF(:,1,j,i);']);
    eval(['oo_.PosteriorIRF.dsge.HPDsup.' name ' = HPDIRF(:,2,j,i);']);
  end
end


if MAX_nirfs_dsgevar
    MeanIRFdsgevar = zeros(options_.irf,nvar,M_.exo_nbr);
    MedianIRFdsgevar = zeros(options_.irf,nvar,M_.exo_nbr);
    VarIRFdsgevar = zeros(options_.irf,nvar,M_.exo_nbr);
    DistribIRFdsgevar = zeros(options_.irf,9,nvar,M_.exo_nbr);
    HPDIRFdsgevar = zeros(options_.irf,2,nvar,M_.exo_nbr);    
    fprintf('MH: Posterior (bvar-dsge) IRFs...\n');
    tit(M_.exo_names_orig_ord,:) = M_.exo_names;
    kdx = 0;
    for file = 1:NumberOfIRFfiles_dsgevar
        load([MhDirectoryName '/' M_.fname '_IRF_BVARDSGEs' int2str(file)]);
        for i = 1:M_.exo_nbr
            for j = 1:nvar
                for k = 1:size(STOCK_IRF_BVARDSGE,1)
                    kk = k+kdx;
                    [MeanIRFdsgevar(kk,j,i),MedianIRFdsgevar(kk,j,i),VarIRFdsgevar(kk,j,i),...
                     HPDIRFdsgevar(kk,:,j,i),DistribIRFdsgevar(kk,:,j,i)] = ...
                        posterior_moments(squeeze(STOCK_IRF_BVARDSGE(k,j,i,:)),0);%SelecVariables(j)
                end
            end
        end
        kdx = kdx + size(STOCK_IRF_BVARDSGE,1);
    end
    clear STOCK_IRF_BVARDSGE; 
    for i = 1:M_.exo_nbr
        for j = 1:nvar
            name = [deblank(M_.endo_names(SelecVariables(j),:)) '_' deblank(tit(i,:))];
            eval(['oo_.PosteriorIRF.bvardsge.Mean.' name ' = MeanIRFdsgevar(:,j,i);']);
            eval(['oo_.PosteriorIRF.bvardsge.Median.' name ' = MedianIRFdsgevar(:,j,i);']);
            eval(['oo_.PosteriorIRF.bvardsge.Var.' name ' = VarIRFdsgevar(:,j,i);']);
            eval(['oo_.PosteriorIRF.bvardsge.Distribution.' name ' = DistribIRFdsgevar(:,:,j,i);']);
            eval(['oo_.PosteriorIRF.bvardsge.HPDinf.' name ' = HPDIRFdsgevar(:,1,j,i);']);
            eval(['oo_.PosteriorIRF.bvardsge.HPDsup.' name ' = HPDIRFdsgevar(:,2,j,i);']);
        end
    end
end
%%
%% 	Finally I build the plots.
%%
if options_.TeX
  fidTeX = fopen([DirectoryName '/' M_.fname '_BayesianIRF.TeX'],'w');
  fprintf(fidTeX,'%% TeX eps-loader file generated by PosteriorIRF.m (Dynare).\n');
  fprintf(fidTeX,['%% ' datestr(now,0) '\n']);
  fprintf(fidTeX,' \n');
  titTeX(M_.exo_names_orig_ord,:) = M_.exo_names_tex;
end
%%
subplotnum = 0;
for i=1:M_.exo_nbr
  NAMES = [];
  if options_.TeX
    TEXNAMES = [];
  end
  figunumber = 0;
  for j=1:nvar
    if max(abs(MeanIRF(:,j,i))) > 10^(-6)
      subplotnum = subplotnum+1;
      if options_.nograph
        if subplotnum == 1 & options_.relative_irf
          hh = figure('Name',['Relative response to orthogonalized shock to ' tit(i,:)],'Visible','off');
        elseif subplotnum == 1 & ~options_.relative_irf
          hh = figure('Name',['Orthogonalized shock to ' tit(i,:)],'Visible','off');
        end
      else
        if subplotnum == 1 & options_.relative_irf
          hh = figure('Name',['Relative response to orthogonalized shock to ' tit(i,:)]);
        elseif subplotnum == 1 & ~options_.relative_irf
          hh = figure('Name',['Orthogonalized shock to ' tit(i,:)]);
        end
      end
      set(0,'CurrentFigure',hh)
      subplot(nn,nn,subplotnum);
      if ~MAX_nirfs_dsgevar
          h1 = area(1:options_.irf,HPDIRF(:,2,j,i));
          set(h1,'FaceColor',[.9 .9 .9]);
          set(h1,'BaseValue',min(HPDIRF(:,1,j,i)));
          hold on
          h2 = area(1:options_.irf,HPDIRF(:,1,j,i),'FaceColor',[1 1 1],'BaseValue',min(HPDIRF(:,1,j,i)));
          set(h2,'FaceColor',[1 1 1]);
          set(h2,'BaseValue',min(HPDIRF(:,1,j,i)));
          plot(1:options_.irf,MeanIRF(:,j,i),'-k','linewidth',3)
          % plot([1 options_.irf],[0 0],'-r','linewidth',0.5);          
          box on
          axis tight
          xlim([1 options_.irf]);
          hold off
      else    
          h1 = area(1:options_.irf,HPDIRF(:,2,j,i));
          set(h1,'FaceColor',[.9 .9 .9]);
          set(h1,'BaseValue',min([min(HPDIRF(:,1,j,i)),min(HPDIRFdsgevar(:,1,j,i))]));
          hold on;
          h2 = area(1:options_.irf,HPDIRF(:,1,j,i));
          set(h2,'FaceColor',[1 1 1]);
          set(h2,'BaseValue',min([min(HPDIRF(:,1,j,i)),min(HPDIRFdsgevar(:,1,j,i))]));
          plot(1:options_.irf,MeanIRF(:,j,i),'-k','linewidth',3)
          % plot([1 options_.irf],[0 0],'-r','linewidth',0.5);
          plot(1:options_.irf,MeanIRFdsgevar(:,j,i),'--k','linewidth',2)
          plot(1:options_.irf,HPDIRFdsgevar(:,1,j,i),'--k','linewidth',1)
          plot(1:options_.irf,HPDIRFdsgevar(:,2,j,i),'--k','linewidth',1)
          box on
          axis tight
          xlim([1 options_.irf]);
          hold off
      end
      name = deblank(varlist(j,:));
      NAMES = strvcat(NAMES,name);
      if options_.TeX
        texname = deblank(varlist_TeX(j,:));
        TEXNAMES = strvcat(TEXNAMES,['$' texname '$']);
      end
      title(name,'Interpreter','none')
    end
    if subplotnum == MaxNumberOfPlotPerFigure | (j == nvar  & subplotnum> 0)
      figunumber = figunumber+1;
      set(hh,'visible','on')
      eval(['print -depsc2 ' DirectoryName '/'  M_.fname '_Bayesian_IRF_' deblank(tit(i,:)) '_' int2str(figunumber)]);
      eval(['print -dpdf ' DirectoryName '/' M_.fname  '_Bayesian_IRF_' deblank(tit(i,:)) '_' int2str(figunumber)]);
      saveas(hh,[DirectoryName '/' M_.fname  '_Bayesian_IRF_' deblank(tit(i,:))  '_' int2str(figunumber) '.fig']);
      set(hh,'visible','off')
      if options_.nograph, close(hh), end
      if options_.TeX
        fprintf(fidTeX,'\\begin{figure}[H]\n');
        for jj = 1:size(TEXNAMES,1)
          fprintf(fidTeX,['\\psfrag{%s}[1][][0.5][0]{%s}\n'],deblank(NAMES(jj,:)),deblank(TEXNAMES(jj,:)));
        end    
        fprintf(fidTeX,'\\centering \n');
        fprintf(fidTeX,'\\includegraphics[scale=0.5]{%s_Bayesian_IRF_%s}\n',M_.fname,deblank(tit(i,:)));
        if options_.relative_irf
          fprintf(fidTeX,['\\caption{Bayesian relative IRF.}']);
        else
          fprintf(fidTeX,'\\caption{Bayesian IRF.}');
        end
        fprintf(fidTeX,'\\label{Fig:BayesianIRF:%s}\n',deblank(tit(i,:)));
        fprintf(fidTeX,'\\end{figure}\n');
        fprintf(fidTeX,' \n');
      end
      subplotnum = 0;
    end
  end% loop over selected endo_var
end% loop over exo_var  
%%
if options_.TeX
  fprintf(fidTeX,'%% End of TeX file.\n');
  fclose(fidTeX);
end
fprintf('MH: Posterior IRFs, done!\n');