Merge branch 'OccBin_posterior' into 'master'

 OccBin: disable incompatible options

See merge request Dynare/dynare!2352

doc/manual/source/the-model-file.rst

@@ -7718,7 +7718,7 @@ observed variables.
        Triggers the computation of the posterior distribution of
        IRFs. The length of the IRFs are controlled by the ``irf``
        option. Results are stored in ``oo_.PosteriorIRF.dsge`` (see
-       below for a description of this variable).
+       below for a description of this variable). Not compatible with OccBin.
     .. option:: relative_irf
@@ -8066,7 +8066,7 @@ observed variables.
        stored in ``oo_.PosteriorTheoreticalMoments`` (see
        :mvar:`oo_.PosteriorTheoreticalMoments`). The number of lags in
        the autocorrelation function is controlled by the ``ar``
-       option.
+       option. Not compatible with OccBin.
     .. option:: contemporaneous_correlation
@@ -8151,7 +8151,7 @@ observed variables.
        the posterior mode. If a Metropolis-Hastings is computed, the
        distribution of forecasts is stored in variables
        ``oo_.PointForecast`` and ``oo_.MeanForecast``. See
-       :ref:`fore`, for a description of these variables.
+       :ref:`fore`, for a description of these variables. Not compatible with OccBin.
     .. option:: tex

matlab/estimation/dynare_estimation_1.m

@@ -520,8 +520,12 @@ if issmc(options_) || (any(bayestopt_.pshape>0) && options_.mh_replic) ||  (any(
                 if error_flag
                     error('%s: I cannot compute the posterior IRFs!',dispString)
                 end
+                if options_.occbin.likelihood.status
+                    fprintf('%s: the bayesian_irf option is not compatible with the use of OccBin.',dispString)
+                else
                     oo_=PosteriorIRF('posterior',options_,estim_params_,oo_,M_,bayestopt_,dataset_,dataset_info,dispString);
                 end                
+            end
             if options_.moments_varendo
                 if error_flag
                     error('%s: I cannot compute the posterior moments for the endogenous variables!',dispString)
@@ -549,8 +553,12 @@ if issmc(options_) || (any(bayestopt_.pshape>0) && options_.mh_replic) ||  (any(
                         end
                     end
                 end
+                if options_.occbin.likelihood.status
+                    fprintf('%s: the moments_varendo option is not compatible with the use of OccBin.',dispString)
+                else
                     oo_ = compute_moments_varendo('posterior',options_,M_,oo_,estim_params_,var_list_);
                 end
+            end
             if options_.smoother || ~isempty(options_.filter_step_ahead) || options_.forecast
                 if error_flag
                     error('%s: I cannot compute the posterior statistics!',dispString)

matlab/estimation/initial_estimation_checks.m

@@ -86,6 +86,15 @@ if options_.occbin.likelihood.status || options_.occbin.smoother.status
     if options_.fast_kalman_filter
         error('initial_estimation_checks:: Occbin is incompatible with the fast Kalman filter.')        
     end
+    if options_.bayesian_irf
+        error('initial_estimation_checks:: Occbin is incompatible with the bayesian_irf option.')                
+    end
+    if options_.moments_varendo
+        error('initial_estimation_checks:: Occbin is incompatible with the moments_varendo option.')                
+    end
+    if options_.forecast
+        error('initial_estimation_checks:: Occbin is incompatible with the forecast option.')
+    end
 end
 
 if (options_.occbin.likelihood.status && options_.occbin.likelihood.inversion_filter) || (options_.occbin.smoother.status && options_.occbin.smoother.inversion_filter)

matlab/estimation/prior_posterior_statistics_core.m

@@ -76,7 +76,7 @@ naK=myinputs.naK;
 horizon=myinputs.horizon;
 iendo=myinputs.iendo;
 IdObs=myinputs.IdObs; %index of observables
-if horizon
+if horizon && ~options_.occbin.smoother.status
     i_last_obs=myinputs.i_last_obs;
     MAX_nforc1=myinputs.MAX_nforc1;
     MAX_nforc2=myinputs.MAX_nforc2;
@@ -168,7 +168,7 @@ if run_smoother
     stock_smoothed_constant=NaN(endo_nbr,gend,MAX_n_smoothed_constant);
     stock_smoothed_trend=NaN(endo_nbr,gend,MAX_n_smoothed_trend);
     stock_trend_coeff = zeros(endo_nbr,MAX_n_trend_coeff);
-    if horizon
+    if horizon && ~options_.occbin.smoother.status
         stock_forcst_mean= NaN(endo_nbr,horizon,MAX_nforc1);
         stock_forcst_point = NaN(endo_nbr,horizon,MAX_nforc2);
         if ~isequal(M_.H,0)
@@ -328,7 +328,7 @@ for b=fpar:B
                 end
             end
         end
-        if horizon
+        if horizon && ~options_.occbin.smoother.status
             yyyy = alphahat(iendo,i_last_obs);
             yf = simulate_posterior_forecasts(yyyy,dr,horizon,false,M_.Sigma_e,1);
             if options_.prefilter
@@ -563,7 +563,7 @@ dyn_waitbar_close(h);
 
 
 function yf=simulate_posterior_forecasts(y0,dr,horizon,stochastic_indicator,Sigma_e,n)
-% function yf=forcst2(y0,horizon,dr,n)
+% function yf=simulate_posterior_forecasts(y0,horizon,dr,n)
 %
 % computes forecasts based on first order model solution, given shocks
 % drawn from the shock distribution, but not including measurement error