Commit ad0c2926 authored by Stéphane Adjemian's avatar Stéphane Adjemian
Browse files

Cosmetic. Renamed DsgeVarLikelihood as dsge_var_likelihood.

parent 9238523c
......@@ -189,7 +189,7 @@ while fpar<B
end
if MAX_nirfs_dsgevar
IRUN = IRUN+1;
[fval,junk1,junk2,cost_flag,info,PHI,SIGMAu,iXX] = DsgeVarLikelihood(deep',dataset_,options_,M_,estim_params_,bayestopt_,oo_);
[fval,junk1,junk2,cost_flag,info,PHI,SIGMAu,iXX] = dsge_var_likelihood(deep',dataset_,options_,M_,estim_params_,bayestopt_,oo_);
dsge_prior_weight = M_.params(strmatch('dsge_prior_weight',M_.param_names));
DSGE_PRIOR_WEIGHT = floor(dataset_.info.ntobs*(1+dsge_prior_weight));
SIGMA_inv_upper_chol = chol(inv(SIGMAu*dataset_.info.ntobs*(dsge_prior_weight+1)));
......
......@@ -100,7 +100,7 @@ f=f0;
H=H0;
cliff=0;
while ~done
% penalty for dsge_likelihood and DsgeVarLikelihood
% penalty for dsge_likelihood and dsge_var_likelihood
objective_function_penalty_base = f;
g1=[]; g2=[]; g3=[];
......
function [fval,grad,hess,exit_flag,info,PHI,SIGMAu,iXX,prior] = DsgeVarLikelihood(xparam1,DynareDataset,DynareOptions,Model,EstimatedParameters,BayesInfo,DynareResults)
function [fval,grad,hess,exit_flag,info,PHI,SIGMAu,iXX,prior] = dsge_var_likelihood(xparam1,DynareDataset,DynareOptions,Model,EstimatedParameters,BayesInfo,DynareResults)
% Evaluates the posterior kernel of the bvar-dsge model.
%
% INPUTS
......
......@@ -47,7 +47,7 @@ if ~options_.noconstant
bvar.NumberOfVariables;
end
[fval,cost_flag,info,PHI,SIGMAu,iXX,prior] = DsgeVarLikelihood(deep',DynareDataset,DynareOptions,Model,EstimatedParameters,BayesInfo,DynareResults);
[fval,cost_flag,info,PHI,SIGMAu,iXX,prior] = dsge_var_likelihood(deep',DynareDataset,DynareOptions,Model,EstimatedParameters,BayesInfo,DynareResults);
% Conditionnal posterior density of the lagged matrices (given Sigma) ->
% Matric-variate normal distribution.
......
......@@ -75,7 +75,7 @@ if ~options_.dsge_var
objective_function = str2func('dsge_likelihood');
end
else
objective_function = str2func('DsgeVarLikelihood');
objective_function = str2func('dsge_var_likelihood');
end
[dataset_,xparam1, hh, M_, options_, oo_, estim_params_,bayestopt_] = dynare_estimation_init(var_list_, dname, [], M_, options_, oo_, estim_params_, bayestopt_);
......
......@@ -106,7 +106,7 @@ if ~noprint
error('The model violates one (many) endogenous prior restriction(s)')
case 51
error('You are estimating a DSGE-VAR model, but the value of the dsge prior weight is too low!')
case 52 %DsgeVarLikelihood
case 52 %dsge_var_likelihood
error('');
case 61 %Discretionary policy
error(['Discretionary policy: maximum number of iterations has been reached. Procedure failed. ']);
......
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