Display changes in line with meetings in Paris (not yet 100% completed):
- simplified; - first rank deficiency; - why rank deficiency; - some info about weak identification (not completed);time-shift
Marco Ratto
parent
8852bd1b09
commit
0a637be94c
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@ -1,4 +1,4 @@
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function disp_identification(pdraws, idemodel, idemoments, disp_pcorr)
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function disp_identification(pdraws, idemodel, idemoments, name, advanced)
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% Copyright (C) 2008-2010 Dynare Team
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%
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@ -17,10 +17,10 @@ function disp_identification(pdraws, idemodel, idemoments, disp_pcorr)
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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 <http://www.gnu.org/licenses/>.
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global bayestopt_
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global options_
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if nargin<4 | isempty(disp_pcorr),
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disp_pcorr=0;
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if nargin<5 | isempty(advanced),
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advanced=0;
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end
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[SampleSize, npar] = size(pdraws);
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@ -28,24 +28,18 @@ jok = 0;
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jokP = 0;
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jokJ = 0;
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jokPJ = 0;
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if ~any(any(idemodel.ind==0))
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disp(['All parameters are identified in the model in the MC sample (rank of H).' ]),
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disp(' ')
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end
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if ~any(any(idemoments.ind==0))
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disp(['All parameters are identified by J moments in the MC sample (rank of J)' ]),
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end
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for j=1:npar,
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if any(idemodel.ind(j,:)==0),
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pno = 100*length(find(idemodel.ind(j,:)==0))/SampleSize;
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disp(['Parameter ',bayestopt_.name{j},' is not identified in the model for ',num2str(pno),'% of MC runs!' ])
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disp(' ')
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end
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if any(idemoments.ind(j,:)==0),
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pno = 100*length(find(idemoments.ind(j,:)==0))/SampleSize;
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disp(['Parameter ',bayestopt_.name{j},' is not identified by J moments for ',num2str(pno),'% of MC runs!' ])
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disp(' ')
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end
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% if any(idemodel.ind(j,:)==0),
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% pno = 100*length(find(idemodel.ind(j,:)==0))/SampleSize;
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% disp(['Parameter ',name{j},' is not identified in the model for ',num2str(pno),'% of MC runs!' ])
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% disp(' ')
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% end
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% if any(idemoments.ind(j,:)==0),
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% pno = 100*length(find(idemoments.ind(j,:)==0))/SampleSize;
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% disp(['Parameter ',name{j},' is not identified by J moments for ',num2str(pno),'% of MC runs!' ])
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% disp(' ')
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% end
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if any(idemodel.ind(j,:)==1),
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iok = find(idemodel.ind(j,:)==1);
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jok = jok+1;
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@ -89,14 +83,32 @@ for j=1:npar,
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end
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dyntable('Multi collinearity in the model:',char('param','min','mean','max'), ...
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char(bayestopt_.name(kok)),[mmin, mmean, mmax],10,10,6);
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disp(' ')
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if any(idemodel.ino),
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disp('WARNING !!!')
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if SampleSize>1,
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disp(['The rank of H (model) is deficient for ', num2str(length(find(idemodel.ino))/SampleSize*100),'% of MC runs!' ]),
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else
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disp(['The rank of H (model) is deficient!' ]),
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end
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end
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for j=1:npar,
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if any(idemodel.ind(j,:)==0),
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pno = 100*length(find(idemodel.ind(j,:)==0))/SampleSize;
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if SampleSize>1
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disp([name{j},' is not identified in the model for ',num2str(pno),'% of MC runs!' ])
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else
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disp([name{j},' is not identified in the model!' ])
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end
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end
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iweak = length(find(idemodel.Mco(j,:)'>(1-1.e-10)));
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if iweak,
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disp('WARNING !!!')
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disp(['Model derivatives of parameter ',bayestopt_.name{j},' are multi-collinear (with tol = 1.e-10) for ',num2str(iweak/SampleSize*100),'% of MC runs!' ])
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% disp('WARNING !!!')
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% disp(['Model derivatives of parameter ',name{j},' are multi-collinear (with tol = 1.e-10) for ',num2str(iweak/SampleSize*100),'% of MC runs!' ])
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if SampleSize>1
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disp([name{j},' is collinear w.r.t. all other params ',num2str(iweak/SampleSize*100),'% of MC runs!' ])
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else
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disp([name{j},' is collinear w.r.t. all other params!' ])
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end
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if npar>(j+1),
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[ipair, jpair] = find(squeeze(idemodel.Pco(j,j+1:end,:))'>(1-1.e-10));
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else
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@ -106,47 +118,102 @@ for j=1:npar,
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for jx=j+1:npar,
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ixp = find(jx==(jpair+j));
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if ~isempty(ixp)
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disp(['Model derivatives of parameters [',bayestopt_.name{j},',',bayestopt_.name{jx},'] are collinear (with tol = 1.e-10) for ',num2str(length(ixp)/SampleSize*100),'% of MC runs!' ])
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if SampleSize > 1,
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disp([' [',name{j},',',name{jx},'] are PAIRWISE collinear (with tol = 1.e-10) for ',num2str(length(ixp)/SampleSize*100),'% of MC runs!' ])
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else
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disp([' [',name{j},',',name{jx},'] are PAIRWISE collinear (with tol = 1.e-10)!' ])
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end
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end
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end
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end
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end
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end
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disp(' ')
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if ~any(idemodel.ino) && ~any(any(idemodel.ind==0))
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disp(['All parameters are identified in the model (rank of H).' ]),
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disp(' ')
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end
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if any(idemoments.ino),
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disp('WARNING !!!')
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if SampleSize > 1,
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disp(['The rank of J (moments) is deficient for ', num2str(length(find(idemoments.ino))/SampleSize*100),'% of MC runs!' ]),
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else
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disp(['The rank of J (moments) is deficient!' ]),
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end
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end
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if any(idemoments.ino),
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% disp('WARNING !!!')
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% disp(['The rank of J (moments) is deficient for ', num2str(length(find(idemoments.ino))/SampleSize*100),'% of MC runs!' ]),
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indno=[];
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for j=1:SampleSize, indno=[indno;idemoments.indno{j}]; end
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freqno = mean(indno)*100;
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ifreq=find(freqno);
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% disp('MOMENT RANK FAILURE DUE TO COLLINEARITY OF PARAMETERS:');
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for j=1:npar,
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if any(idemoments.ind(j,:)==0),
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pno = 100*length(find(idemoments.ind(j,:)==0))/SampleSize;
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if SampleSize > 1
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disp([name{j},' is not identified by J moments for ',num2str(pno),'% of MC runs!' ])
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else
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disp([name{j},' is not identified by J moments!' ])
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end
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end
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iweak = length(find(idemoments.Mco(j,:)'>(1-1.e-10)));
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if iweak,
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% disp('WARNING !!!')
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% disp(['Moment derivatives of parameter ',name{j},' are multi-collinear (with tol = 1.e-10) for ',num2str(iweak/SampleSize*100),'% of MC runs!' ])
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if SampleSize > 1,
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disp([name{j},' is collinear w.r.t. all other params ',num2str(iweak/SampleSize*100),'% of MC runs!' ])
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else
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disp([name{j},' is collinear w.r.t. all other params!' ])
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end
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if npar>(j+1),
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[ipair, jpair] = find(squeeze(idemoments.Pco(j,j+1:end,:))'>(1-1.e-10));
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else
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[ipair, jpair] = find(squeeze(idemoments.Pco(j,j+1:end,:))>(1-1.e-10));
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end
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if ~isempty(jpair),
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for jx=j+1:npar,
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ixp = find(jx==(jpair+j));
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if ~isempty(ixp)
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if SampleSize > 1
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disp([' [',name{j},',',name{jx},'] are PAIRWISE collinear (with tol = 1.e-10) for ',num2str(length(ixp)/SampleSize*100),'% of MC runs!' ])
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else
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disp([' [',name{j},',',name{jx},'] are PAIRWISE collinear (with tol = 1.e-10) !' ])
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end
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end
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end
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end
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end
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end
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end
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if ~any(idemoments.ino) && ~any(any(idemoments.ind==0))
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disp(['All parameters are identified by J moments (rank of J)' ]),
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disp(' ')
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end
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if ~ options_.noprint & advanced,
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disp('Press KEY to continue with identification analysis')
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pause;
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dyntable('Multi collinearity in the model:',char('param','min','mean','max'), ...
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char(name(kok)),[mmin, mmean, mmax],10,10,6);
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disp(' ')
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dyntable('Multi collinearity for moments in J:',char('param','min','mean','max'), ...
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char(bayestopt_.name(kokJ)),[mminJ, mmeanJ, mmaxJ],10,10,6);
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char(name(kokJ)),[mminJ, mmeanJ, mmaxJ],10,10,6);
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disp(' ')
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for j=1:npar,
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iweak = length(find(idemoments.Mco(j,:)'>(1-1.e-10)));
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if iweak,
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disp('WARNING !!!')
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disp(['Moment derivatives of parameter ',bayestopt_.name{j},' are multi-collinear (with tol = 1.e-10) for ',num2str(iweak/SampleSize*100),'% of MC runs!' ])
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if npar>(j+1),
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[ipair, jpair] = find(squeeze(idemoments.Pco(j,j+1:end,:))'>(1-1.e-10));
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else
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[ipair, jpair] = find(squeeze(idemoments.Pco(j,j+1:end,:))>(1-1.e-10));
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end
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if ~isempty(jpair),
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for jx=j+1:npar,
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ixp = find(jx==(jpair+j));
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if ~isempty(ixp)
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disp(['Moment derivatives of parameters [',bayestopt_.name{j},',',bayestopt_.name{jx},'] are collinear (with tol = 1.e-10) for ',num2str(length(ixp)/SampleSize*100),'% of MC runs!' ])
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end
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end
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end
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end
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end
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disp(' ')
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if disp_pcorr,
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for j=1:length(kokP),
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dyntable([bayestopt_.name{kokP(j)},' pairwise correlations in the model'],char(' ','min','mean','max'), ...
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char(bayestopt_.name{jpM{j}}),[pminM{j}' pmeanM{j}' pmaxM{j}'],10,10,3);
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end
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% if advanced & (~options_.noprint),
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% for j=1:length(kokP),
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% dyntable([name{kokP(j)},' pairwise correlations in the model'],char(' ','min','mean','max'), ...
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% char(name{jpM{j}}),[pminM{j}' pmeanM{j}' pmaxM{j}'],10,10,3);
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% end
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%
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% for j=1:length(kokPJ),
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% dyntable([name{kokPJ(j)},' pairwise correlations in J moments'],char(' ','min','mean','max'), ...
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% char(name{jpJ{j}}),[pminJ{j}' pmeanJ{j}' pmaxJ{j}'],10,10,3);
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% end
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% end
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% disp(' ')
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for j=1:length(kokPJ),
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dyntable([bayestopt_.name{kokPJ(j)},' pairwise correlations in J moments'],char(' ','min','mean','max'), ...
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char(bayestopt_.name{jpJ{j}}),[pminJ{j}' pmeanJ{j}' pmaxJ{j}'],10,10,3);
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end
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end
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