Fixed bug in set_prior.m when correlations are estimated. Corrected description in header of prior_bounds.m
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c74b1d1bdc
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c2ce75aa45
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@ -4,7 +4,7 @@ function bounds = prior_bounds(bayestopt,options)
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%! @deftypefn {Function File} {@var{bounds} =} prior_bounds (@var{bayesopt},@var{option})
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%! @deftypefn {Function File} {@var{bounds} =} prior_bounds (@var{bayesopt},@var{option})
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%! @anchor{prior_bounds}
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%! @anchor{prior_bounds}
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%! @sp 1
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%! @sp 1
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%! Returns bounds for the prior densities. For each estimated parameter the upper and lower bounds
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%! Returns bounds for the prior densities. For each estimated parameter the lower and upper bounds
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%! are such that the defined intervals contains a probability mass equal to 1-2*@var{option}.prior_trunc. The
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%! are such that the defined intervals contains a probability mass equal to 1-2*@var{option}.prior_trunc. The
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%! default value for @var{option}.prior_trunc is 1e-10 (set in @ref{global_initialization}).
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%! default value for @var{option}.prior_trunc is 1e-10 (set in @ref{global_initialization}).
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%! @sp 2
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%! @sp 2
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@ -43,7 +43,7 @@ function bounds = prior_bounds(bayestopt,options)
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% bayestopt [structure] characterizing priors (shape, mean, p1..p4)
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% bayestopt [structure] characterizing priors (shape, mean, p1..p4)
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%
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%
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% OUTPUTS
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% OUTPUTS
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% bounds [double] matrix specifying prior bounds (row= parameter, column=upper&lower bound)
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% bounds [double] matrix specifying prior bounds (row= parameter, column=lower&upper bound)
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%
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%
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% SPECIAL REQUIREMENTS
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% SPECIAL REQUIREMENTS
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% none
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% none
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@ -106,9 +106,9 @@ if ncx
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bayestopt_.p3 = [ bayestopt_.p3; estim_params_.corrx(:,9)];
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bayestopt_.p3 = [ bayestopt_.p3; estim_params_.corrx(:,9)];
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bayestopt_.p4 = [ bayestopt_.p4; estim_params_.corrx(:,10)];
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bayestopt_.p4 = [ bayestopt_.p4; estim_params_.corrx(:,10)];
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bayestopt_.jscale = [ bayestopt_.jscale; estim_params_.corrx(:,11)];
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bayestopt_.jscale = [ bayestopt_.jscale; estim_params_.corrx(:,11)];
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bayestopt_.name = [bayestopt_.name; cellstr(['corr ' ...
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bayestopt_.name = [bayestopt_.name; cellstr([repmat('corr ',ncx,1)...
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deblank(M_.exo_names(estim_params_.corrx(:,1),:)) ...
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deblank(M_.exo_names(estim_params_.corrx(:,1),:)) ...
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', ' , deblank(M_.exo_names(estim_params_.corrx(:,2),:))])];
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repmat(', ',ncx,1) , deblank(M_.exo_names(estim_params_.corrx(:,2),:))])];
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end
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end
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if ncn
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if ncn
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if isequal(M_.H,0)
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if isequal(M_.H,0)
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@ -124,9 +124,9 @@ if ncn
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bayestopt_.p3 = [ bayestopt_.p3; estim_params_.corrn(:,9)];
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bayestopt_.p3 = [ bayestopt_.p3; estim_params_.corrn(:,9)];
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bayestopt_.p4 = [ bayestopt_.p4; estim_params_.corrn(:,10)];
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bayestopt_.p4 = [ bayestopt_.p4; estim_params_.corrn(:,10)];
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bayestopt_.jscale = [ bayestopt_.jscale; estim_params_.corrn(:,11)];
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bayestopt_.jscale = [ bayestopt_.jscale; estim_params_.corrn(:,11)];
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bayestopt_.name = [bayestiopt_.name; cellstr(['corr ' ...
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bayestopt_.name = [bayestopt_.name; cellstr([repmat('corr ',ncn,1) ...
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deblank(M_.exo_names(estim_params_.corrn(:,1),:)) ...
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deblank(M_.exo_names(estim_params_.corrn(:,1),:)) ...
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', ' , deblank(M_.exo_names(estim_params_.corrn(:,2),:))])];
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repmat(', ',ncn,1) , deblank(M_.exo_names(estim_params_.corrn(:,2),:))])];
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end
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end
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if np
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if np
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xparam1 = [xparam1; estim_params_.param_vals(:,2)];
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xparam1 = [xparam1; estim_params_.param_vals(:,2)];
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