Removed globals from set_all_parameters routine.

matlab/DsgeSmoother.m

@@ -62,7 +62,7 @@ decomp        = [];
 nobs            = size(options_.varobs,1);
 smpl          = size(Y,2);
 
-set_all_parameters(xparam1);
+M_ = set_all_parameters(xparam1,estim_params_,M_);
 
 %------------------------------------------------------------------------------
 % 2. call model setup & reduction program

matlab/PosteriorFilterSmootherAndForecast.m

@@ -135,7 +135,7 @@ end
 for b=1:B
     %deep = GetOneDraw(NumberOfDraws,FirstMhFile,LastMhFile,FirstLine,MAX_nruns,DirectoryName);
     [deep, logpo] = GetOneDraw(type);
-    set_all_parameters(deep);
+    M_ = set_all_parameters(deep,estim_params_,M_);
     [dr,info,M_,options_,oo_] = resol(0,M_,options_,oo_);
     [alphahat,etahat,epsilonhat,ahat,SteadyState,trend_coeff,aK] = ...
         DsgeSmoother(deep,gend,Y,data_index);

matlab/dynare_estimation_1.m

@@ -890,7 +890,7 @@ if (any(bayestopt_.pshape  >0 ) && options_.mh_replic) || ...
             prior_posterior_statistics('posterior',dataset_);
         end
         xparam = get_posterior_parameters('mean');
-        set_all_parameters(xparam);
+        M_ = set_all_parameters(xparam,estim_params_,M_);
     end
 end
 

matlab/get_prior_info.m

@@ -108,7 +108,7 @@ end
 M_.dname = M_.fname;
 
 if info==1% Prior simulations (BK).
-    results = prior_sampler(0,M_,bayestopt_,options_,oo_);
+    results = prior_sampler(0,M_,bayestopt_,options_,oo_,estim_params_);
     % Display prior mass info
     disp(['Prior mass = ' num2str(results.prior.mass)])
     disp(['BK indeterminacy share                = ' num2str(results.bk.indeterminacy_share)])

matlab/gsa/filt_mc_.m

@@ -112,12 +112,12 @@ else
 end
 if ~loadSA,
     if exist('xparam1','var')
-        set_all_parameters(xparam1);
+        M_ = set_all_parameters(xparam1,estim_params_,M_);
         steady_(M_,options_,oo_);
         ys_mode=oo_.steady_state;
     end
     if exist('xparam1_mean','var')
-        set_all_parameters(xparam1_mean);
+        M_ = set_all_parameters(xparam1_mean,estim_params_,M_);
         steady_(M_,options_,oo_);
         ys_mean=oo_.steady_state;
     end

matlab/identification_analysis.m

@@ -48,7 +48,7 @@ persistent indH indJJ indLRE
 nparam=length(params);
 np=length(indx);
 offset=nparam-np;
-set_all_parameters(params);
+M_ = set_all_parameters(params,estim_params_,M_);
 
 nlags = options_ident.ar;
 useautocorr = options_ident.useautocorr;

matlab/prior_analysis.m

@@ -1,4 +1,4 @@
-function oo_ = prior_analysis(type,arg1,arg2,arg3,options_,M_,oo_)  
+function oo_ = prior_analysis(type,arg1,arg2,arg3,options_,M_,oo_,estim_params_)
 % Copyright (C) 2009 Dynare Team
 %
 % This file is part of Dynare.
@@ -28,7 +28,7 @@ switch info
         drsave=1;
     end
     load([M_.dname '/prior/definition.mat']);
-    prior_sampler(drsave,M_,bayestopt_,options_,oo_);
+    prior_sampler(drsave,M_,bayestopt_,options_,oo_,estim_params_);
     clear('bayestopt_');
     oo_ = job(type,SampleSize,arg1,arg2,arg3,options_,M_,oo_);
   case {4,5}

matlab/prior_posterior_statistics_core.m

@@ -149,7 +149,7 @@ for b=fpar:B
             logpo = evaluate_posterior_kernel(deep');
         end
     end
-    set_all_parameters(deep);
+    M_ = set_all_parameters(deep,estim_params_,M_);
     [dr,info,M_,options_,oo_] = resol(0,M_,options_,oo_);
 
     if run_smoother

matlab/prior_sampler.m

@@ -1,4 +1,4 @@
-function results = prior_sampler(drsave,M_,bayestopt_,options_,oo_)
+function results = prior_sampler(drsave,M_,bayestopt_,options_,oo_,estim_params_)
 % This function builds a (big) prior sample.
 %
 % INPUTS
@@ -79,7 +79,7 @@ file_indx_number = 0;
 while iteration < NumberOfSimulations
     loop_indx = loop_indx+1;
     params = prior_draw();
-    set_all_parameters(params);
+    M_ = set_all_parameters(params,estim_params_,M_);
     [dr,INFO,M_,options_,oo_] = resol(work,M_,options_,oo_);
     switch INFO(1)
       case 0

matlab/set_all_parameters.m

@@ -1,18 +1,39 @@
-function set_all_parameters(xparam1)
+function M = set_all_parameters(xparam1,estim_params,M)
 
-% function set_all_parameters(xparam1)
+%@info:
-% Sets parameters value 
+%! @deftypefn {Function File} {@var{M} =} dynSeries (@var{xparams1},@var{estim_params},@var{M})
-% 
+%! @anchor{set_all_parameters}
-% INPUTS
+%! @sp 1
-%    xparam1:   vector of parameters to be estimated (initial values)
+%! Update parameter values (deep parameters and covariance matrices).
-%    
+%! @sp 2
-% OUTPUTS
+%! @strong{Inputs}
-%    none
+%! @sp 1
-%        
+%! @table @ @var
-% SPECIAL REQUIREMENTS
+%! @item xparam1
-%    none
+%! N*1 vector of doubles, the values of the N estimated parameters.
+%! @item estim_params
+%! Dynare structure describing the estimated parameters.
+%! @item M
+%! Dynare structure describing the model.
+%! @end table
+%! @sp 1
+%! @strong{Outputs}
+%! @sp 1
+%! @table @ @var
+%! @item M
+%! Dynare structure describing the model, with updated parameters and covariances matrices.
+%! @end table
+%! @sp 2
+%! @strong{This function is called by:}
+%! @sp 1
+%! @ref{DsgeSmoother}, @ref{dynare_estimation_1}, @ref{@@gsa/filt_mc_}, @ref{identification_analysis}, @ref{PosteriorFilterSmootherAndForecast}, @ref{prior_posterior_statistics_core}, @ref{prior_sampler}
+%! @sp 2
+%! @strong{This function calls:}
+%! @sp 2
+%! @end deftypefn
+%@eod:
 
-% Copyright (C) 2003-2009 Dynare Team
+% Copyright (C) 2003-2009, 2012 Dynare Team
 %
 % This file is part of Dynare.
 %
@@ -29,19 +50,17 @@ function set_all_parameters(xparam1)
 % You should have received a copy of the GNU General Public License
 % along with Dynare.  If not, see <http://www.gnu.org/licenses/>.
 
-global estim_params_ M_
+nvx = estim_params.nvx;
-
+ncx = estim_params.ncx;
-nvx = estim_params_.nvx;
+nvn = estim_params.nvn;
-ncx = estim_params_.ncx;
+ncn = estim_params.ncn;
-nvn = estim_params_.nvn;
+np = estim_params.np;
-ncn = estim_params_.ncn;
+Sigma_e = M.Sigma_e;
-np = estim_params_.np;
+H = M.H;
-Sigma_e = M_.Sigma_e;
-H = M_.H;
 
 % setting shocks variance
 if nvx
-    var_exo = estim_params_.var_exo;
+    var_exo = estim_params.var_exo;
     for i=1:nvx
         k =var_exo(i,1);
         Sigma_e(k,k) = xparam1(i)^2;
@@ -52,7 +71,7 @@ offset = nvx;
 
 % setting measument error variance
 if nvn
-    var_endo = estim_params_.var_endo;
+    var_endo = estim_params.var_endo;
     for i=1:nvn
         k = var_endo(i,1);
         H(k,k) = xparam1(i+offset)^2;
@@ -63,16 +82,16 @@ end
 offset = nvx+nvn;
 
 % setting shocks covariances
-if ~isempty(M_.Correlation_matrix)
+if ~isempty(M.Correlation_matrix)
-    Sigma_e = diag(sqrt(diag(Sigma_e)))*M_.Correlation_matrix*diag(sqrt(diag(Sigma_e)));
+    Sigma_e = diag(sqrt(diag(Sigma_e)))*M.Correlation_matrix*diag(sqrt(diag(Sigma_e)));
 end
 if ncx
-    corrx = estim_params_.corrx;
+    corrx = estim_params.corrx;
     for i=1:ncx
         k1 = corrx(i,1);
         k2 = corrx(i,2);
-        M_.Correlation_matrix(k1,k2) = xparam1(i+offset);
+        M.Correlation_matrix(k1,k2) = xparam1(i+offset);
-        M_.Correlation_matrix(k2,k1) = M_.Correlation_matrix(k1,k2);
+        M.Correlation_matrix(k2,k1) = M.Correlation_matrix(k1,k2);
         Sigma_e(k1,k2) = xparam1(i+offset)*sqrt(Sigma_e(k1,k1)*Sigma_e(k2,k2));
         Sigma_e(k2,k1) = Sigma_e(k1,k2);
     end
@@ -82,7 +101,7 @@ end
 offset = nvx+nvn+ncx;
 % setting measurement error covariances
 if ncn
-    corrn = estim_params_.corrn;
+    corrn = estim_params.corrn;
     for i=1:ncn
         k1 = corr(i,1);
         k2 = corr(i,2);
@@ -96,13 +115,13 @@ offset = nvx+ncx+nvn+ncn;
 % setting structural parameters
 %
 if np
-    M_.params(estim_params_.param_vals(:,1)) = xparam1(offset+1:end);
+    M.params(estim_params.param_vals(:,1)) = xparam1(offset+1:end);
 end
 
-% updating matrices in M_
+% updating matrices in M
-if nvx
+if nvx || ncx
-    M_.Sigma_e = Sigma_e;
+    M.Sigma_e = Sigma_e;
 end
 if nvn
-    M_.H = H;
+    M.H = H;
-end
+end