Merge pull request #1134 from JohannesPfeifer/bvar_mdd
Save marginal data density from BVAR in oo_time-shift
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5a91b601a2
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@ -499,7 +499,7 @@ The syntax for computing the marginal density is:
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The options are those described above.
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The options are those described above.
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The command will actually compute the marginal density for several models: first for the model with one lag, then with two lags, and so on up to \textit{max\_number\_of\_lags} lags.
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The command will actually compute the marginal density for several models: first for the model with one lag, then with two lags, and so on up to \textit{max\_number\_of\_lags} lags. Results will be stored in a \textit{max\_number\_of\_lags} by 1 vector \texttt{oo\_.bvar.log\_marginal\_data\_density}.
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\subsection{Forecasting}
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\subsection{Forecasting}
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@ -29,6 +29,10 @@ function bvar_density(maxnlags)
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% You should have received a copy of the GNU General Public License
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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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% along with Dynare. If not, see <http://www.gnu.org/licenses/>.
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global oo_
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oo_.bvar.log_marginal_data_density=NaN(maxnlags,1);
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for nlags = 1:maxnlags
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for nlags = 1:maxnlags
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[ny, nx, posterior, prior] = bvar_toolbox(nlags);
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[ny, nx, posterior, prior] = bvar_toolbox(nlags);
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@ -39,6 +43,8 @@ for nlags = 1:maxnlags
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log_dnsty = posterior_int - prior_int - 0.5*ny*lik_nobs*log(2*pi);
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log_dnsty = posterior_int - prior_int - 0.5*ny*lik_nobs*log(2*pi);
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oo_.bvar.log_marginal_data_density(nlags)=log_dnsty;
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skipline()
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skipline()
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fprintf('The marginal log density of the BVAR(%g) model is equal to %10.4f\n', ...
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fprintf('The marginal log density of the BVAR(%g) model is equal to %10.4f\n', ...
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nlags, log_dnsty);
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nlags, log_dnsty);
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