497 lines
17 KiB
Matlab
497 lines
17 KiB
Matlab
function x0 = stab_map_(OutputDirectoryName)
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%
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% function x0 = stab_map_(OutputDirectoryName)
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%
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% Mapping of stability regions in the prior ranges applying
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% Monte Carlo filtering techniques.
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%
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% INPUTS (from opt_gsa structure)
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% Nsam = MC sample size
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% fload = 0 to run new MC; 1 to load prevoiusly generated analysis
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% alpha2 = significance level for bivariate sensitivity analysis
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% [abs(corrcoef) > alpha2]
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% prepSA = 1: save transition matrices for mapping reduced form
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% = 0: no transition matrix saved (default)
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% pprior = 1: sample from prior ranges (default): sample saved in
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% _prior.mat file
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% = 0: sample from posterior ranges: sample saved in
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% _mc.mat file
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% OUTPUT:
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% x0: one parameter vector for which the model is stable.
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%
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% GRAPHS
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% 1) Pdf's of marginal distributions under the stability (dotted
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% lines) and unstability (solid lines) regions
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% 2) Cumulative distributions of:
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% - stable subset (dotted lines)
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% - unacceptable subset (solid lines)
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% 3) Bivariate plots of significant correlation patterns
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% ( abs(corrcoef) > alpha2) under the stable and unacceptable subsets
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%
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% USES lptauSEQ,
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% stab_map_1, stab_map_2
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%
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% Part of the Sensitivity Analysis Toolbox for DYNARE
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%
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% Written by Marco Ratto, 2006
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% Joint Research Centre, The European Commission,
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% (http://eemc.jrc.ec.europa.eu/),
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% marco.ratto@jrc.it
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%
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% Disclaimer: This software is not subject to copyright protection and is in the public domain.
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% It is an experimental system. The Joint Research Centre of European Commission
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% assumes no responsibility whatsoever for its use by other parties
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% and makes no guarantees, expressed or implied, about its quality, reliability, or any other
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% characteristic. We would appreciate acknowledgement if the software is used.
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% Reference:
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% M. Ratto, Global Sensitivity Analysis for Macroeconomic models, MIMEO, 2006.
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%
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%global bayestopt_ estim_params_ dr_ options_ ys_ fname_
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global bayestopt_ estim_params_ options_ oo_ M_
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opt_gsa=options_.opt_gsa;
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Nsam = opt_gsa.Nsam;
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fload = opt_gsa.load_stab;
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ksstat = opt_gsa.ksstat;
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alpha2 = opt_gsa.alpha2_stab;
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prepSA = (opt_gsa.redform | opt_gsa.identification);
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pprior = opt_gsa.pprior;
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ilptau = opt_gsa.ilptau;
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nliv = opt_gsa.morris_nliv;
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ntra = opt_gsa.morris_ntra;
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dr_ = oo_.dr;
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%if isfield(dr_,'ghx'),
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ys_ = oo_.dr.ys;
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nspred = dr_.nspred; %size(dr_.ghx,2);
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nboth = dr_.nboth;
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nfwrd = dr_.nfwrd;
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%end
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fname_ = M_.fname;
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nshock = estim_params_.nvx;
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nshock = nshock + estim_params_.nvn;
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nshock = nshock + estim_params_.ncx;
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nshock = nshock + estim_params_.ncn;
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lpmat0=[];
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pshape = bayestopt_.pshape(nshock+1:end);
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p1 = bayestopt_.p1(nshock+1:end);
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p2 = bayestopt_.p2(nshock+1:end);
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p3 = bayestopt_.p3(nshock+1:end);
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p4 = bayestopt_.p4(nshock+1:end);
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if nargin==0,
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OutputDirectoryName='';
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end
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opt=options_;
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options_.periods=0;
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options_.nomoments=1;
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options_.irf=0;
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options_.noprint=1;
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options_.simul=0;
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if fload==0,
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% if prepSA
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% T=zeros(size(dr_.ghx,1),size(dr_.ghx,2)+size(dr_.ghu,2),Nsam/2);
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% end
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if isfield(dr_,'ghx'),
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egg=zeros(length(dr_.eigval),Nsam);
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end
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yys=zeros(length(dr_.ys),Nsam);
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if opt_gsa.morris
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if opt_gsa.morris == 1
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[lpmat, OutFact] = Sampling_Function_2(nliv, estim_params_.np, ntra, ones(estim_params_.np, 1), zeros(estim_params_.np,1), []);
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lpmat = lpmat.*(nliv-1)/nliv+1/nliv/2;
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Nsam=size(lpmat,1);
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elseif opt_gsa.morris==2
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lpmat = prep_ide(Nsam,estim_params_.np,5);
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Nsam=size(lpmat,1);
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end
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else
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if estim_params_.np<52 & ilptau>0,
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[lpmat] = lptauSEQ(Nsam,estim_params_.np); % lptau
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if estim_params_.np>30 | ilptau==2, % scrambled lptau
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for j=1:estim_params_.np,
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lpmat(:,j)=lpmat(randperm(Nsam),j);
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end
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end
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else ilptau==0
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%[lpmat] = rand(Nsam,estim_params_.np);
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for j=1:estim_params_.np,
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lpmat(:,j) = randperm(Nsam)'./(Nsam+1); %latin hypercube
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end
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end
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end
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prior_draw_gsa(1);
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if pprior,
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for j=1:nshock,
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lpmat0(:,j) = randperm(Nsam)'./(Nsam+1); %latin hypercube
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if opt_gsa.prior_range
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lpmat0(:,j)=lpmat0(:,j).*(bayestopt_.ub(j)-bayestopt_.lb(j))+bayestopt_.lb(j);
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end
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end
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if opt_gsa.prior_range
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for j=1:estim_params_.np,
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lpmat(:,j)=lpmat(:,j).*(bayestopt_.ub(j+nshock)-bayestopt_.lb(j+nshock))+bayestopt_.lb(j+nshock);
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end
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else
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xx=prior_draw_gsa(0,[lpmat0 lpmat]);
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lpmat0=xx(:,1:nshock);
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lpmat=xx(:,nshock+1:end);
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clear xx;
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end
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else
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% for j=1:nshock,
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% xparam1(j) = oo_.posterior_mode.shocks_std.(bayestopt_.name{j});
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% sd(j) = oo_.posterior_std.shocks_std.(bayestopt_.name{j});
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% lpmat0(:,j) = randperm(Nsam)'./(Nsam+1); %latin hypercube
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% lb = max(bayestopt_.lb(j), xparam1(j)-2*sd(j));
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% ub1=xparam1(j)+(xparam1(j) - lb); % define symmetric range around the mode!
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% ub = min(bayestopt_.ub(j),ub1);
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% if ub<ub1,
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% lb=xparam1(j)-(ub-xparam1(j)); % define symmetric range around the mode!
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% end
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% lpmat0(:,j) = lpmat0(:,j).*(ub-lb)+lb;
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% end
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% %
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% for j=1:estim_params_.np,
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% xparam1(j+nshock) = oo_.posterior_mode.parameters.(bayestopt_.name{j+nshock});
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% sd(j+nshock) = oo_.posterior_std.parameters.(bayestopt_.name{j+nshock});
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% lb = max(bayestopt_.lb(j+nshock),xparam1(j+nshock)-2*sd(j+nshock));
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% ub1=xparam1(j+nshock)+(xparam1(j+nshock) - lb); % define symmetric range around the mode!
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% ub = min(bayestopt_.ub(j+nshock),ub1);
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% if ub<ub1,
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% lb=xparam1(j+nshock)-(ub-xparam1(j+nshock)); % define symmetric range around the mode!
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% end
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% %ub = min(bayestopt_.ub(j+nshock),xparam1(j+nshock)+2*sd(j+nshock));
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% if estim_params_.np>30 & estim_params_.np<52
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% lpmat(:,j) = lpmat(randperm(Nsam),j).*(ub-lb)+lb;
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% else
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% lpmat(:,j) = lpmat(:,j).*(ub-lb)+lb;
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% end
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% end
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%load([fname_,'_mode'])
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eval(['load ' options_.mode_file ';']');
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d = chol(inv(hh));
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lp=randn(Nsam*2,nshock+estim_params_.np)*d+kron(ones(Nsam*2,1),xparam1');
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for j=1:Nsam*2,
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lnprior(j) = any(lp(j,:)'<=bayestopt_.lb | lp(j,:)'>=bayestopt_.ub);
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end
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ireal=[1:2*Nsam];
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ireal=ireal(find(lnprior==0));
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lp=lp(ireal,:);
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Nsam=min(Nsam, length(ireal));
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lpmat0=lp(1:Nsam,1:nshock);
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lpmat=lp(1:Nsam,nshock+1:end);
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clear lp lnprior ireal;
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end
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%
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h = waitbar(0,'Please wait...');
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istable=[1:Nsam];
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jstab=0;
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iunstable=[1:Nsam];
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iindeterm=zeros(1,Nsam);
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iwrong=zeros(1,Nsam);
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for j=1:Nsam,
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M_.params(estim_params_.param_vals(:,1)) = lpmat(j,:)';
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%try stoch_simul([]);
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try
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[Tt,Rr,SteadyState,info] = dynare_resolve(bayestopt_.restrict_var_list,...
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bayestopt_.restrict_columns,...
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bayestopt_.restrict_aux);
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if ~exist('T')
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T=zeros(size(dr_.ghx,1),size(dr_.ghx,2)+size(dr_.ghu,2),Nsam);
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end
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catch
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if isfield(oo_.dr,'eigval'),
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oo_.dr=rmfield(oo_.dr,'eigval');
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end
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if isfield(oo_.dr,'ghx'),
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oo_.dr=rmfield(oo_.dr,'ghx');
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end
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disp('No solution could be found'),
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end
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dr_ = oo_.dr;
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if isfield(dr_,'ghx'),
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egg(:,j) = sort(dr_.eigval);
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iunstable(j)=0;
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if prepSA
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jstab=jstab+1;
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T(:,:,jstab) = [dr_.ghx dr_.ghu];
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[A,B] = ghx2transition(squeeze(T(:,:,jstab)), ...
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bayestopt_.restrict_var_list, ...
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bayestopt_.restrict_columns, ...
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bayestopt_.restrict_aux);
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end
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if ~exist('nspred'),
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nspred = dr_.nspred; %size(dr_.ghx,2);
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nboth = dr_.nboth;
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nfwrd = dr_.nfwrd;
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end
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else
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istable(j)=0;
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if isfield(dr_,'eigval')
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egg(:,j) = sort(dr_.eigval);
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if exist('nspred')
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if any(isnan(egg(1:nspred,j)))
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iwrong(j)=j;
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else
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if (nboth | nfwrd) & abs(egg(nspred+1,j))<=options_.qz_criterium,
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iindeterm(j)=j;
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end
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end
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end
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else
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if exist('egg'),
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egg(:,j)=ones(size(egg,1),1).*NaN;
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end
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iwrong(j)=j;
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end
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end
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ys_=real(dr_.ys);
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yys(:,j) = ys_;
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ys_=yys(:,1);
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waitbar(j/Nsam,h,['MC iteration ',int2str(j),'/',int2str(Nsam)])
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end
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close(h)
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if prepSA,
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T=T(:,:,1:jstab);
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end
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istable=istable(find(istable)); % stable params
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iunstable=iunstable(find(iunstable)); % unstable params
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iindeterm=iindeterm(find(iindeterm)); % indeterminacy
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iwrong=iwrong(find(iwrong)); % dynare could not find solution
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% % map stable samples
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% istable=[1:Nsam];
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% for j=1:Nsam,
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% if any(isnan(egg(1:nspred,j)))
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% istable(j)=0;
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% else
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% if abs(egg(nspred,j))>=options_.qz_criterium; %(1-(options_.qz_criterium-1)); %1-1.e-5;
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% istable(j)=0;
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% %elseif (dr_.nboth | dr_.nfwrd) & abs(egg(nspred+1,j))<=options_.qz_criterium; %1+1.e-5;
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% elseif (nboth | nfwrd) & abs(egg(nspred+1,j))<=options_.qz_criterium; %1+1.e-5;
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% istable(j)=0;
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% end
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% end
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% end
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% istable=istable(find(istable)); % stable params
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%
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% % map unstable samples
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% iunstable=[1:Nsam];
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% for j=1:Nsam,
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% %if abs(egg(dr_.npred+1,j))>1+1.e-5 & abs(egg(dr_.npred,j))<1-1.e-5;
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% %if (dr_.nboth | dr_.nfwrd),
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% if ~any(isnan(egg(1:5,j)))
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% if (nboth | nfwrd),
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% if abs(egg(nspred+1,j))>options_.qz_criterium & abs(egg(nspred,j))<options_.qz_criterium; %(1-(options_.qz_criterium-1));
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% iunstable(j)=0;
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% end
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% else
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% if abs(egg(nspred,j))<options_.qz_criterium; %(1-(options_.qz_criterium-1));
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% iunstable(j)=0;
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% end
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% end
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% end
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% end
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% iunstable=iunstable(find(iunstable)); % unstable params
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bkpprior.pshape=bayestopt_.pshape;
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bkpprior.p1=bayestopt_.p1;
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bkpprior.p2=bayestopt_.p2;
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bkpprior.p3=bayestopt_.p3;
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bkpprior.p4=bayestopt_.p4;
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if pprior,
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if ~prepSA
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save([OutputDirectoryName '\' fname_ '_prior'], ...
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'bkpprior','lpmat','lpmat0','iunstable','istable','iindeterm','iwrong', ...
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'egg','yys','nspred','nboth','nfwrd')
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else
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save([OutputDirectoryName '\' fname_ '_prior'], ...
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'bkpprior','lpmat','lpmat0','iunstable','istable','iindeterm','iwrong', ...
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'egg','yys','T','nspred','nboth','nfwrd')
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end
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else
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if ~prepSA
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save([OutputDirectoryName '\' fname_ '_mc'], ...
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'lpmat','lpmat0','iunstable','istable','iindeterm','iwrong', ...
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'egg','yys','nspred','nboth','nfwrd')
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else
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save([OutputDirectoryName '\' fname_ '_mc'], ...
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'lpmat','lpmat0','iunstable','istable','iindeterm','iwrong', ...
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'egg','yys','T','nspred','nboth','nfwrd')
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end
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end
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else
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if pprior,
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filetoload=[OutputDirectoryName '\' fname_ '_prior'];
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else
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filetoload=[OutputDirectoryName '\' fname_ '_mc'];
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end
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load(filetoload,'lpmat','lpmat0','iunstable','istable','iindeterm','iwrong','egg','yys','nspred','nboth','nfwrd')
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Nsam = size(lpmat,1);
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if prepSA & isempty(strmatch('T',who('-file', filetoload),'exact')),
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h = waitbar(0,'Please wait...');
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options_.periods=0;
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options_.nomoments=1;
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options_.irf=0;
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options_.noprint=1;
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stoch_simul([]);
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%T=zeros(size(dr_.ghx,1),size(dr_.ghx,2)+size(dr_.ghu,2),length(istable));
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ntrans=length(istable);
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for j=1:ntrans,
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M_.params(estim_params_.param_vals(:,1)) = lpmat(istable(j),:)';
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%stoch_simul([]);
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[Tt,Rr,SteadyState,info] = dynare_resolve(bayestopt_.restrict_var_list,...
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bayestopt_.restrict_columns,...
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bayestopt_.restrict_aux);
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if ~exist('T')
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T=zeros(size(dr_.ghx,1),size(dr_.ghx,2)+size(dr_.ghu,2),ntrans);
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end
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dr_ = oo_.dr;
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T(:,:,j) = [dr_.ghx dr_.ghu];
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if ~exist('nspred')
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nspred = dr_.nspred; %size(dr_.ghx,2);
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nboth = dr_.nboth;
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nfwrd = dr_.nfwrd;
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end
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ys_=real(dr_.ys);
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yys(:,j) = ys_;
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ys_=yys(:,1);
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waitbar(j/ntrans,h,['MC iteration ',int2str(j),'/',int2str(ntrans)])
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end
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close(h)
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save(filetoload,'T','-append')
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elseif prepSA
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load(filetoload,'T')
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end
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end
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if pprior
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aname='prior_stab';
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auname='prior_unacceptable';
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aunstname='prior_unstable';
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aindname='prior_indeterm';
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asname='prior_stable';
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else
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aname='mc_stab';
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auname='mc_unacceptable';
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aunstname='mc_unstable';
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aindname='mc_indeterm';
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asname='mc_stable';
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end
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delete([OutputDirectoryName,'\',fname_,'_',aname,'_*.*']);
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%delete([OutputDirectoryName,'\',fname_,'_',aname,'_SA_*.*']);
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delete([OutputDirectoryName,'\',fname_,'_',asname,'_corr_*.*']);
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delete([OutputDirectoryName,'\',fname_,'_',auname,'_corr_*.*']);
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delete([OutputDirectoryName,'\',fname_,'_',aunstname,'_corr_*.*']);
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delete([OutputDirectoryName,'\',fname_,'_',aindname,'_corr_*.*']);
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if length(iunstable)>0 & length(iunstable)<Nsam,
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disp([num2str(length(istable)/Nsam*100,3),'\% of the prior support is stable.'])
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disp([num2str( (length(iunstable)-length(iwrong)-length(iindeterm) )/Nsam*100),'\% of the prior support is unstable.'])
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if ~isempty(iindeterm),
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disp([num2str(length(iindeterm)/Nsam*100,3),'\% of the prior support gives indeterminacy.'])
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end
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if ~isempty(iwrong),
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disp(' ');
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disp(['For ',num2str(length(iwrong)/Nsam*100,3),'\% of the prior support dynare could not find a solution.'])
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end
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disp(' ');
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% Blanchard Kahn
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[proba, dproba] = stab_map_1(lpmat, istable, iunstable, aname,0);
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indstab=find(dproba>ksstat);
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disp('Smirnov statistics in driving acceptable behaviour')
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for j=1:estim_params_.np,
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disp([M_.param_names(estim_params_.param_vals(j,1),:),' d-stat = ', num2str(dproba(j),3)])
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end
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disp(' ');
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if ~isempty(indstab)
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stab_map_1(lpmat, istable, iunstable, aname, 1, indstab, OutputDirectoryName);
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end
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ixun=iunstable(find(~ismember(iunstable,[iindeterm,iwrong])));
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if ~isempty(iindeterm),
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[proba, dproba] = stab_map_1(lpmat, [1:Nsam], iindeterm, [aname, '_indet'],0);
|
|
indindet=find(dproba>ksstat);
|
|
disp('Smirnov statistics in driving indeterminacy')
|
|
for j=1:estim_params_.np,
|
|
disp([M_.param_names(estim_params_.param_vals(j,1),:),' d-stat = ', num2str(dproba(j),3)])
|
|
end
|
|
disp(' ');
|
|
if ~isempty(indindet)
|
|
stab_map_1(lpmat, istable, iindeterm, [aname, '_indet'], 1, indindet, OutputDirectoryName);
|
|
end
|
|
end
|
|
|
|
if ~isempty(ixun),
|
|
[proba, dproba] = stab_map_1(lpmat, [1:Nsam], ixun, [aname, '_unst'],0);
|
|
indunst=find(dproba>ksstat);
|
|
disp('Smirnov statistics in driving instability')
|
|
for j=1:estim_params_.np,
|
|
disp([M_.param_names(estim_params_.param_vals(j,1),:),' d-stat = ', num2str(dproba(j),3)])
|
|
end
|
|
disp(' ');
|
|
if ~isempty(indunst)
|
|
stab_map_1(lpmat, istable, ixun, [aname, '_unst'], 1, indunst, OutputDirectoryName);
|
|
end
|
|
end
|
|
|
|
disp(' ')
|
|
disp('Starting bivariate analysis:')
|
|
|
|
c0=corrcoef(lpmat(istable,:));
|
|
c00=tril(c0,-1);
|
|
|
|
stab_map_2(lpmat(istable,:),alpha2, asname, OutputDirectoryName);
|
|
if length(iunstable)>3,
|
|
stab_map_2(lpmat(iunstable,:),alpha2, auname, OutputDirectoryName);
|
|
end
|
|
if length(iindeterm)>3,
|
|
stab_map_2(lpmat(iindeterm,:),alpha2, aindname, OutputDirectoryName);
|
|
end
|
|
if length(ixun)>3,
|
|
stab_map_2(lpmat(ixun,:),alpha2, aunstname, OutputDirectoryName);
|
|
end
|
|
|
|
x0=0.5.*(bayestopt_.ub(1:nshock)-bayestopt_.lb(1:nshock))+bayestopt_.lb(1:nshock);
|
|
x0 = [x0; lpmat(istable(1),:)'];
|
|
if istable(end)~=Nsam
|
|
M_.params(estim_params_.param_vals(:,1)) = lpmat(istable(1),:)';
|
|
stoch_simul([]);
|
|
end
|
|
else
|
|
if length(iunstable)==0,
|
|
disp('All parameter values in the specified ranges are stable!')
|
|
x0=0.5.*(bayestopt_.ub(1:nshock)-bayestopt_.lb(1:nshock))+bayestopt_.lb(1:nshock);
|
|
x0 = [x0; lpmat(istable(1),:)'];
|
|
else
|
|
disp('All parameter values in the specified ranges are not acceptable!')
|
|
x0=[];
|
|
end
|
|
|
|
end
|
|
|
|
|
|
options_.periods=opt.periods;
|
|
if isfield(opt,'nomoments'),
|
|
options_.nomoments=opt.nomoments;
|
|
end
|
|
options_.irf=opt.irf;
|
|
options_.noprint=opt.noprint;
|
|
if isfield(opt,'simul'),
|
|
options_.simul=opt.simul;
|
|
end
|
|
|
|
|
|
|