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Include prior info in penalty with Bayesian estimation. 

This can improve a bit optimization routines when parameter go beyond prior bounds during line search algorithms or when numerical gradient is computed.
time-shift
Marco Ratto 2012-05-31 14:44:16 +02:00
parent 32c6c50d9c
commit dc7c0fa74d
1 changed files with 10 additions and 1 deletions
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11
matlab/dsge_likelihood.m
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@ -141,7 +141,7 @@ function [fval,DLIK,Hess,exit_flag,ys,trend_coeff,info,Model,DynareOptions,Bayes
% In summary, an initial call to the present function, without triggering
% any condition, guarantees that 'penalty' is properly initialized when needed.
persistent penalty
persistent penalty prior_penalty
% Initialization of the returned variables and others...
fval = [];
@ -180,6 +180,10 @@ end
if ~isequal(DynareOptions.mode_compute,1) && any(xparam1<BayesInfo.lb)
k = find(xparam1<BayesInfo.lb);
fval = penalty+sum((BayesInfo.lb(k)-xparam1(k)).^2);
xtemp=xparam1;
xtemp(k)=BayesInfo.lb(k);
prior_correction = max(0,-prior_penalty-priordens(xtemp,BayesInfo.pshape,BayesInfo.p6,BayesInfo.p7,BayesInfo.p3,BayesInfo.p4));
fval = fval+prior_correction;
exit_flag = 0;
info = 41;
if analytic_derivation,
@ -192,6 +196,10 @@ end
if ~isequal(DynareOptions.mode_compute,1) && any(xparam1>BayesInfo.ub)
k = find(xparam1>BayesInfo.ub);
fval = penalty+sum((xparam1(k)-BayesInfo.ub(k)).^2);
xtemp=xparam1;
xtemp(k)=BayesInfo.ub(k);
prior_correction = max(0,-prior_penalty -priordens(xtemp,BayesInfo.pshape,BayesInfo.p6,BayesInfo.p7,BayesInfo.p3,BayesInfo.p4));
fval = fval+prior_correction;
exit_flag = 0;
info = 42;
if analytic_derivation,
@ -749,6 +757,7 @@ DynareOptions.kalman_algo = kalman_algo;
% Update the penalty.
penalty = fval;
prior_penalty = -lnprior;
if analytic_derivation==0 && nargout==2,
lik=lik(start:end,:);