diff --git a/matlab/DsgeLikelihood.m b/matlab/DsgeLikelihood.m
index 54489fb29..d34d997ac 100644
--- a/matlab/DsgeLikelihood.m
+++ b/matlab/DsgeLikelihood.m
@@ -476,10 +476,10 @@ if ((kalman_algo==1) || (kalman_algo==3))% Multivariate Kalman Filter
         end
         if analytic_derivation
             if no_DLIK==0
-                [DLIK] = score(T,R,Q,H,Pstar,Y,DT,DYss,DOm,DH,DP,start,mf,kalman_tol,riccati_tol);
+                [DLIK] = score(T,R,Q,H,Pstar,Y,DT,DYss,DOm,DH,DP,start,Z,kalman_tol,riccati_tol);
             end
-            if nargout==7
-                [AHess] = AHessian(T,R,Q,H,Pstar,Y,DT,DYss,DOm,DH,DP,start,mf,kalman_tol,riccati_tol);
+            if nargout==11
+                [AHess] = AHessian(T,R,Q,H,Pstar,Y,DT,DYss,DOm,DH,DP,start,Z,kalman_tol,riccati_tol);
             end
         end
     else
diff --git a/matlab/dynare_estimation_init.m b/matlab/dynare_estimation_init.m
index e9c6754f2..5751f6730 100644
--- a/matlab/dynare_estimation_init.m
+++ b/matlab/dynare_estimation_init.m
@@ -312,9 +312,9 @@ end % if ~isempty(options_.unit_root_vars)
 % Test if the data file is declared.
 if isempty(options_.datafile)
     if gsa_flag
-        data = [];
-        rawdata = [];
-        data_info = [];
+        dataset_ = [];
+%         rawdata = [];
+%         data_info = [];
         return
     else
         error('datafile option is missing')
diff --git a/matlab/dynare_identification.m b/matlab/dynare_identification.m
index 024260f56..d9b95388c 100644
--- a/matlab/dynare_identification.m
+++ b/matlab/dynare_identification.m
@@ -114,14 +114,26 @@ options_.nomoments=0;
 options_ = set_default_option(options_,'datafile',[]);
 options_.mode_compute = 0;
 options_.plot_priors = 0;
-[data,rawdata,xparam1,data_info]=dynare_estimation_init(M_.endo_names,fname_,1);
-if isempty(data_info),
-    data_info.gend = periods;
-    data_info.data = [];
-    data_info.data_index = [];
-    data_info.number_of_observations = periods*size(options_.varobs,1);
-    data_info.no_more_missing_observations = 0;
-    data_info.missing_value = 0;
+[dataset_,xparam1, M_, options_, oo_, estim_params_,bayestopt_]=dynare_estimation_init(M_.endo_names,fname_,1, M_, options_, oo_, estim_params_, bayestopt_);
+if isempty(dataset_),
+    dataset_.info.ntobs = periods;
+    dataset_.info.nvobs = rows(options_.varobs);
+    dataset_.info.varobs = options_.varobs;
+    dataset_.rawdata = [];
+    dataset_.missing.state = 0;
+    dataset_.missing.aindex = [];
+    dataset_.missing.vindex = [];
+    dataset_.missing.number_of_observations = [];
+    dataset_.missing.no_more_missing_observations = [];
+    dataset_.descriptive.mean = [];
+    dataset_.data = [];
+
+%     data_info.gend = periods;
+%     data_info.data = [];
+%     data_info.data_index = [];
+%     data_info.number_of_observations = periods*size(options_.varobs,1);
+%     data_info.no_more_missing_observations = 0;
+%     data_info.missing_value = 0;
 end
 
 % results = prior_sampler(0,M_,bayestopt_,options_,oo_);
@@ -240,7 +252,7 @@ if iload <=0,
         disp('Testing current parameter values')
     end
     [idehess_point, idemoments_point, idemodel_point, idelre_point, derivatives_info_point] = ...
-        identification_analysis(params,indx,indexo,options_ident,data_info, prior_exist, name_tex,1);
+        identification_analysis(params,indx,indexo,options_ident,dataset_, prior_exist, name_tex,1);
     idehess_point.params=params;
 %     siH = idemodel_point.siH;
 %     siJ = idemoments_point.siJ;
@@ -274,7 +286,7 @@ if iload <=0,
             params = prior_draw();
         end
         [dum1, ideJ, ideH, ideGP, dum2 , info] = ...
-            identification_analysis(params,indx,indexo,options_MC,data_info, prior_exist, name_tex,0);
+            identification_analysis(params,indx,indexo,options_MC,dataset_, prior_exist, name_tex,0);
         if iteration==0,
             MAX_tau   = min(SampleSize,ceil(MaxNumberOfBytes/(size(ideH.siH,1)*nparam)/8));
             stoH = zeros([size(ideH.siH,1),nparam,MAX_tau]);
@@ -429,10 +441,10 @@ if SampleSize > 1,
                 fprintf('\n')
                 tittxt = 'Draw with HIGHEST condition number';
                 fprintf('\n')
-                disp(['Testing ',tittxt, '. Press ENTER']), pause,
+                disp(['Testing ',tittxt, '. Press ENTER']), pause(5),
                 if ~iload,
                     [idehess_max, idemoments_max, idemodel_max, idelre_max, derivatives_info_max] = ...
-                        identification_analysis(pdraws(jmax,:),indx,indexo,options_ident,data_info, prior_exist, name_tex,1);
+                        identification_analysis(pdraws(jmax,:),indx,indexo,options_ident,dataset_, prior_exist, name_tex,1);
                     save([IdentifDirectoryName '/' M_.fname '_identif.mat'], 'idehess_max', 'idemoments_max','idemodel_max', 'idelre_max', 'jmax', '-append');
                 end
                 disp_identification(pdraws(jmax,:), idemodel_max, idemoments_max, name);
@@ -442,10 +454,10 @@ if SampleSize > 1,
                 fprintf('\n')
                 tittxt = 'Draw with SMALLEST condition number';
                 fprintf('\n')
-                disp(['Testing ',tittxt, '. Press ENTER']), pause,
+                disp(['Testing ',tittxt, '. Press ENTER']), pause(5),
                 if ~iload,
                     [idehess_min, idemoments_min, idemodel_min, idelre_min, derivatives_info_min] = ...
-                        identification_analysis(pdraws(jmin,:),indx,indexo,options_ident,data_info, prior_exist, name_tex,1);
+                        identification_analysis(pdraws(jmin,:),indx,indexo,options_ident,dataset_, prior_exist, name_tex,1);
                     save([IdentifDirectoryName '/' M_.fname '_identif.mat'], 'idehess_min', 'idemoments_min','idemodel_min', 'idelre_min', 'jmin', '-append');
                 end
                 disp_identification(pdraws(jmin,:), idemodel_min, idemoments_min, name);
@@ -455,10 +467,10 @@ if SampleSize > 1,
                 for j=1:length(jcrit),
                     tittxt = ['Rank deficient draw n. ',int2str(j)];
                     fprintf('\n')
-                    disp(['Testing ',tittxt, '. Press ENTER']), pause,
+                    disp(['Testing ',tittxt, '. Press ENTER']), pause(5),
                     if ~iload,
                         [idehess_(j), idemoments_(j), idemodel_(j), idelre_(j), derivatives_info_(j)] = ...
-                            identification_analysis(pdraws(jcrit(j),:),indx,indexo,options_ident,data_info, prior_exist, name_tex,1);
+                            identification_analysis(pdraws(jcrit(j),:),indx,indexo,options_ident,dataset_, prior_exist, name_tex,1);
                     end
                     disp_identification(pdraws(jcrit(j),:), idemodel_(j), idemoments_(j), name);
                     close all,
diff --git a/matlab/identification_analysis.m b/matlab/identification_analysis.m
index e571bb1a7..af9074c4d 100644
--- a/matlab/identification_analysis.m
+++ b/matlab/identification_analysis.m
@@ -129,13 +129,14 @@ if info(1)==0,
             options_.irf = 0;
             options_.noprint = 1;
             options_.order = 1;
-            options_.periods = data_info.gend+100;
+            options_.periods = data_info.info.ntobs+100;
             options_.kalman_algo = 1;
             info = stoch_simul(options_.varobs);
-            datax=oo_.endo_simul(options_.varobs_id,100+1:end);
+            data_info.data=oo_.endo_simul(options_.varobs_id,100+1:end);
             %                         datax=data;
             derivatives_info.no_DLIK=1;
-            [fval,cost_flag,ys,trend_coeff,info,DLIK,AHess] = DsgeLikelihood(params',data_info.gend,datax,data_info.data_index,data_info.number_of_observations,data_info.no_more_missing_observations,derivatives_info);
+            [fval,cost_flag,ys,trend_coeff,info,M_,options_,bayestopt_,oo_,DLIK,AHess] = DsgeLikelihood(params',data_info,options_,M_,estim_params_,bayestopt_,oo_,derivatives_info);
+%                 fval = DsgeLikelihood(xparam1,data_info,options_,M_,estim_params_,bayestopt_,oo_);
             AHess=-AHess;
             ide_hess.AHess= AHess;
             deltaM = sqrt(diag(AHess));
diff --git a/matlab/plot_identification.m b/matlab/plot_identification.m
index e499f337d..e2d533322 100644
--- a/matlab/plot_identification.m
+++ b/matlab/plot_identification.m
@@ -94,7 +94,7 @@ if SampleSize == 1,
     
     if advanced,
         disp(' ')
-        disp('Press ENTER to display advanced diagnostics'), pause,
+        disp('Press ENTER to display advanced diagnostics'), pause(5),
         figure('Name',[tittxt, ' - Sensitivity plot']),
         subplot(211)
         mmm = (siJnorm)'./max(siJnorm);
@@ -258,7 +258,7 @@ else
     if options_.nograph, close(gcf); end
     if advanced,
         disp(' ')
-        disp('Press ENTER to display advanced diagnostics'), pause,
+        disp('Press ENTER to display advanced diagnostics'), pause(5),
         options_.nograph=1;
         figure('Name','MC Condition Number'),
         subplot(221)