322 lines
11 KiB
Matlab
322 lines
11 KiB
Matlab
function prior_posterior_statistics(type,Y,gend,data_index,missing_value)
|
|
|
|
% function PosteriorFilterSmootherAndForecast(Y,gend, type)
|
|
% Computes posterior filter smoother and forecasts
|
|
%
|
|
% INPUTS
|
|
% type: posterior
|
|
% prior
|
|
% gsa
|
|
% Y: data
|
|
% gend: number of observations
|
|
% data_index [cell] 1*smpl cell of column vectors of indices.
|
|
% missing_value 1 if missing values, 0 otherwise
|
|
%
|
|
% OUTPUTS
|
|
% none
|
|
%
|
|
% SPECIAL REQUIREMENTS
|
|
% none
|
|
|
|
% Copyright (C) 2005-2008 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 <http://www.gnu.org/licenses/>.
|
|
|
|
global options_ estim_params_ oo_ M_ bayestopt_
|
|
|
|
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;
|
|
naK = length(options_.filter_step_ahead);
|
|
%%
|
|
MaxNumberOfBytes=options_.MaxNumberOfBytes;
|
|
endo_nbr=M_.endo_nbr;
|
|
exo_nbr=M_.exo_nbr;
|
|
nvobs = size(options_.varobs,1);
|
|
iendo = 1:endo_nbr;
|
|
horizon = options_.forecast;
|
|
% moments_varendo = options_.moments_varendo;
|
|
filtered_vars = options_.filtered_vars;
|
|
if horizon
|
|
i_last_obs = gend+(1-M_.maximum_endo_lag:0);
|
|
end
|
|
maxlag = M_.maximum_endo_lag;
|
|
%%
|
|
DirectoryName = CheckPath('metropolis');
|
|
load([ DirectoryName '/' M_.fname '_mh_history'])
|
|
FirstMhFile = record.KeepedDraws.FirstMhFile;
|
|
FirstLine = record.KeepedDraws.FirstLine;
|
|
TotalNumberOfMhFiles = sum(record.MhDraws(:,2)); LastMhFile = TotalNumberOfMhFiles;
|
|
TotalNumberOfMhDraws = sum(record.MhDraws(:,1));
|
|
NumberOfDraws = TotalNumberOfMhDraws-floor(options_.mh_drop*TotalNumberOfMhDraws);
|
|
clear record;
|
|
if ~isempty(options_.subdraws)
|
|
B = options_.subdraws;
|
|
if B > NumberOfDraws
|
|
B = NumberOfDraws;
|
|
end
|
|
else
|
|
B = min(1200, round(0.25*NumberOfDraws));
|
|
end
|
|
|
|
%%
|
|
MAX_nruns = min(B,ceil(MaxNumberOfBytes/(npar+2)/8));
|
|
MAX_nsmoo = min(B,ceil(MaxNumberOfBytes/((endo_nbr)*gend)/8));
|
|
MAX_ninno = min(B,ceil(MaxNumberOfBytes/(exo_nbr*gend)/8));
|
|
MAX_nerro = min(B,ceil(MaxNumberOfBytes/(size(options_.varobs,1)*gend)/8));
|
|
if naK
|
|
MAX_naK = min(B,ceil(MaxNumberOfBytes/(size(options_.varobs,1)* ...
|
|
length(options_.filter_step_ahead)*gend)/8));
|
|
end
|
|
if horizon
|
|
MAX_nforc1 = min(B,ceil(MaxNumberOfBytes/((endo_nbr)*(horizon+maxlag))/8));
|
|
MAX_nforc2 = min(B,ceil(MaxNumberOfBytes/((endo_nbr)*(horizon+maxlag))/ ...
|
|
8));
|
|
IdObs = bayestopt_.mfys;
|
|
|
|
end
|
|
MAX_momentsno = min(B,ceil(MaxNumberOfBytes/(get_moments_size(options_)*8)));
|
|
%%
|
|
varlist = options_.varlist;
|
|
if isempty(varlist)
|
|
varlist = M_.endo_names;
|
|
SelecVariables = transpose(1:M_.endo_nbr);
|
|
nvar = M_.endo_nbr;
|
|
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
|
|
end
|
|
|
|
irun = ones(7,1);
|
|
ifil = zeros(7,1);
|
|
|
|
if exist('OCTAVE_VERSION')
|
|
diary off;
|
|
else
|
|
h = waitbar(0,'Taking subdraws...');
|
|
end
|
|
|
|
stock_param = zeros(MAX_nruns, npar);
|
|
stock_logpo = zeros(MAX_nruns,1);
|
|
stock_ys = zeros(MAX_nruns,endo_nbr);
|
|
run_smoother = 0;
|
|
if options_.smoother
|
|
stock_smooth = zeros(endo_nbr,gend,MAX_nsmoo);
|
|
stock_innov = zeros(exo_nbr,gend,B);
|
|
stock_error = zeros(nvobs,gend,MAX_nerro);
|
|
stock_update = zeros(endo_nbr,gend,MAX_nsmoo);
|
|
run_smoother = 1;
|
|
end
|
|
|
|
if options_.filter_step_ahead
|
|
stock_filter_step_ahead = zeros(naK,endo_nbr,gend+ ...
|
|
options_.filter_step_ahead(end),MAX_naK);
|
|
run_smoother = 1;
|
|
end
|
|
if options_.forecast
|
|
stock_forcst_mean = zeros(endo_nbr,horizon+maxlag,MAX_nforc1);
|
|
stock_forcst_point = zeros(endo_nbr,horizon+maxlag,MAX_nforc2);
|
|
run_smoother = 1;
|
|
end
|
|
%if moments_varendo
|
|
% stock_moments = cell(MAX_momentsno,1);
|
|
%end
|
|
for b=1:B
|
|
[deep, logpo] = GetOneDraw(type);
|
|
set_all_parameters(deep);
|
|
dr = resol(oo_.steady_state,0);
|
|
|
|
%if moments_varendo
|
|
% stock_moments{irun(8)} = compute_model_moments(dr,M_,options_);
|
|
%end
|
|
|
|
if run_smoother
|
|
[alphahat,etahat,epsilonhat,alphatilde,SteadyState,trend_coeff,aK] = ...
|
|
DsgeSmoother(deep,gend,Y,data_index,missing_value);
|
|
if options_.loglinear
|
|
stock_smooth(dr.order_var,:,irun(1)) = alphahat(1:endo_nbr,:)+ ...
|
|
repmat(log(dr.ys(dr.order_var)),1,gend);
|
|
stock_update(dr.order_var,:,irun(1)) = alphatilde(1:endo_nbr,:)+ ...
|
|
repmat(log(dr.ys(dr.order_var)),1,gend);
|
|
else
|
|
stock_smooth(dr.order_var,:,irun(1)) = alphahat(1:endo_nbr,:)+ ...
|
|
repmat(dr.ys(dr.order_var),1,gend);
|
|
stock_update(dr.order_var,:,irun(1)) = alphatilde(1:endo_nbr,:)+ ...
|
|
repmat(dr.ys(dr.order_var),1,gend);
|
|
end
|
|
stock_innov(:,:,irun(2)) = etahat;
|
|
if nvn
|
|
stock_error(:,:,irun(3)) = epsilonhat;
|
|
end
|
|
if naK
|
|
stock_filter_step_ahead(:,dr.order_var,:,irun(4)) = aK(options_.filter_step_ahead,1:endo_nbr,:);
|
|
end
|
|
|
|
if horizon
|
|
yyyy = alphahat(iendo,i_last_obs);
|
|
yf = forcst2a(yyyy,dr,zeros(horizon,exo_nbr));
|
|
if options_.prefilter == 1
|
|
yf(:,IdObs) = yf(:,IdObs)+repmat(bayestopt_.mean_varobs', ...
|
|
horizon+maxlag,1);
|
|
end
|
|
yf(:,IdObs) = yf(:,IdObs)+(gend+[1-maxlag:horizon]')*trend_coeff';
|
|
if options_.loglinear == 1
|
|
yf = yf+repmat(log(SteadyState'),horizon+maxlag,1);
|
|
else
|
|
yf = yf+repmat(SteadyState',horizon+maxlag,1);
|
|
end
|
|
yf1 = forcst2(yyyy,horizon,dr,1);
|
|
if options_.prefilter == 1
|
|
yf1(:,IdObs,:) = yf1(:,IdObs,:)+ ...
|
|
repmat(bayestopt_.mean_varobs',[horizon+maxlag,1,1]);
|
|
end
|
|
yf1(:,IdObs,:) = yf1(:,IdObs,:)+repmat((gend+[1-maxlag:horizon]')* ...
|
|
trend_coeff',[1,1,1]);
|
|
if options_.loglinear == 1
|
|
yf1 = yf1 + repmat(log(SteadyState'),[horizon+maxlag,1,1]);
|
|
else
|
|
yf1 = yf1 + repmat(SteadyState',[horizon+maxlag,1,1]);
|
|
end
|
|
|
|
stock_forcst_mean(:,:,irun(6)) = yf';
|
|
stock_forcst_point(:,:,irun(7)) = yf1';
|
|
end
|
|
|
|
end
|
|
stock_param(irun(5),:) = deep;
|
|
stock_logpo(irun(5),1) = logpo;
|
|
stock_ys(irun(5),:) = SteadyState';
|
|
|
|
irun = irun + ones(7,1);
|
|
|
|
if irun(1) > MAX_nsmoo || b == B
|
|
stock = stock_smooth(:,:,1:irun(1)-1);
|
|
ifil(1) = ifil(1) + 1;
|
|
save([DirectoryName '/' M_.fname '_smooth' int2str(ifil(1)) '.mat'],'stock');
|
|
stock = stock_update(:,:,1:irun(1)-1);
|
|
save([DirectoryName '/' M_.fname '_update' int2str(ifil(1)) '.mat'],'stock');
|
|
irun(1) = 1;
|
|
end
|
|
|
|
if irun(2) > MAX_ninno || b == B
|
|
stock = stock_innov(:,:,1:irun(2)-1);
|
|
ifil(2) = ifil(2) + 1;
|
|
save([DirectoryName '/' M_.fname '_inno' int2str(ifil(2)) '.mat'],'stock');
|
|
irun(2) = 1;
|
|
end
|
|
|
|
if nvn && (irun(3) > MAX_nerro || b == B)
|
|
stock = stock_error(:,:,1:irun(3)-1);
|
|
ifil(3) = ifil(3) + 1;
|
|
save([DirectoryName '/' M_.fname '_error' int2str(ifil(3)) '.mat'],'stock');
|
|
irun(3) = 1;
|
|
end
|
|
|
|
if naK && (irun(4) > MAX_naK || b == B)
|
|
stock = stock_filter_step_ahead(:,:,:,1:irun(4)-1);
|
|
ifil(4) = ifil(4) + 1;
|
|
save([DirectoryName '/' M_.fname '_filter_step_ahead' int2str(ifil(4)) '.mat'],'stock');
|
|
irun(4) = 1;
|
|
end
|
|
|
|
if irun(5) > MAX_nruns || b == B
|
|
stock = stock_param(1:irun(5)-1,:);
|
|
ifil(5) = ifil(5) + 1;
|
|
save([DirectoryName '/' M_.fname '_param' int2str(ifil(5)) '.mat'],'stock','stock_logpo','stock_ys');
|
|
irun(5) = 1;
|
|
end
|
|
|
|
if horizon && (irun(6) > MAX_nforc1 || b == B)
|
|
stock = stock_forcst_mean(:,:,1:irun(6)-1);
|
|
ifil(6) = ifil(6) + 1;
|
|
save([DirectoryName '/' M_.fname '_forc_mean' int2str(ifil(6)) '.mat'],'stock');
|
|
irun(6) = 1;
|
|
end
|
|
|
|
if horizon && (irun(7) > MAX_nforc2 || b == B)
|
|
stock = stock_forcst_point(:,:,1:irun(7)-1);
|
|
ifil(7) = ifil(7) + 1;
|
|
save([DirectoryName '/' M_.fname '_forc_point' int2str(ifil(7)) '.mat'],'stock');
|
|
irun(7) = 1;
|
|
end
|
|
|
|
% if moments_varendo && (irun(8) > MAX_momentsno || b == B)
|
|
% stock = stock_moments(1:irun(8)-1);
|
|
% ifil(8) = ifil(8) + 1;
|
|
% save([DirectoryName '/' M_.fname '_moments' int2str(ifil(8)) '.mat'],'stock');
|
|
% irun(8) = 1;
|
|
% end
|
|
|
|
if exist('OCTAVE_VERSION')
|
|
printf('Taking subdraws: %3.f%% done\r', b/B);
|
|
else
|
|
waitbar(b/B,h);
|
|
end
|
|
end
|
|
|
|
if exist('OCTAVE_VERSION')
|
|
printf('\n');
|
|
diary on;
|
|
else
|
|
close(h)
|
|
end
|
|
|
|
stock_gend=gend;
|
|
stock_data=Y;
|
|
save([DirectoryName '/' M_.fname '_data.mat'],'stock_gend','stock_data');
|
|
|
|
if options_.smoother
|
|
pm3(endo_nbr,gend,ifil(1),B,'Smoothed variables',...
|
|
'',M_.endo_names,'tit_tex',M_.endo_names,...
|
|
varlist,'SmoothedVariables',[M_.dname '/metropolis'],'_smooth');
|
|
pm3(exo_nbr,gend,ifil(2),B,'Smoothed shocks',...
|
|
'',M_.exo_names,'tit_tex',M_.exo_names,...
|
|
M_.exo_names,'SmoothedShocks',[M_.dname '/metropolis'],'_inno');
|
|
if nvn
|
|
% needs to be fixed
|
|
% pm3(endo_nbr,gend,ifil(3),B,'Smoothed measurement errors',...
|
|
% M_.endo_names(SelecVariables),M_.endo_names,'tit_tex',M_.endo_names,...
|
|
% 'names2','smooth_errors',[M_.fname '/metropolis'],'_error')
|
|
end
|
|
end
|
|
|
|
if options_.filtered_vars
|
|
pm3(endo_nbr,gend,ifil(1),B,'Updated Variables',...
|
|
'',M_.endo_names,'tit_tex',M_.endo_names,...
|
|
varlist,'UpdatedVariables',[M_.dname '/metropolis'], ...
|
|
'_update');
|
|
pm3(endo_nbr,gend+1,ifil(4),B,'One step ahead forecast',...
|
|
'',M_.endo_names,'tit_tex',M_.endo_names,...
|
|
varlist,'FilteredVariables',[M_.dname '/metropolis'],'_filter_step_ahead');
|
|
end
|
|
|
|
if options_.forecast
|
|
pm3(endo_nbr,horizon+maxlag,ifil(6),B,'Forecasted variables (mean)',...
|
|
'',M_.endo_names,'tit_tex',M_.endo_names,...
|
|
varlist,'MeanForecast',[M_.dname '/metropolis'],'_forc_mean');
|
|
pm3(endo_nbr,horizon+maxlag,ifil(6),B,'Forecasted variables (point)',...
|
|
'',M_.endo_names,'tit_tex',M_.endo_names,...
|
|
varlist,'PointForecast',[M_.dname '/metropolis'],'_forc_point');
|
|
end |