74 lines
3.1 KiB
Matlab
74 lines
3.1 KiB
Matlab
function results_struct = geweke_chi2_test(results1,results2,results_struct,options)
|
|
% results_struct = geweke_chi2_test(results1,results2,results_struct,options)
|
|
% PURPOSE: computes Geweke's chi-squared test for two sets of MCMC sample draws
|
|
%
|
|
% INPUTS
|
|
% results1 [1 by (4+n_taper*2) vector] vector with post. mean,
|
|
% std, NSE_iid, RNE_iid, and tapered NSE and RNE
|
|
% for chain part 1
|
|
% results2 [1 by (4+n_taper*2) vector] vector with post. mean,
|
|
% std, NSE_iid, RNE_iid, and tapered NSE and RNE
|
|
% for chain part 2
|
|
% results_struct [structure] results structure generated by geweke_moments
|
|
% Dynareoptions [structure]
|
|
%
|
|
% OUTPUTS
|
|
% results_struct [structure] containing the following fields:
|
|
% pooled_mean Pooled mean of the chain parts, weighted
|
|
% with precision
|
|
% rpooled_nse Pooled NSE of the chain parts, weighted
|
|
% with precision
|
|
% prob_chi2_test p-value of Chi2-test for equality of
|
|
% means in both chain parts
|
|
% -----------------------------------------------------------------
|
|
|
|
%
|
|
% SPECIAL REQUIREMENTS
|
|
% None.
|
|
|
|
% Copyright (C) 2013-2017 Dynare Team
|
|
%
|
|
% This file is part of Dynare.
|
|
%
|
|
% Dynare is free software: you can redistribute it and/or modify
|
|
% it under the terms of the GNU General Public License as published by
|
|
% the Free Software Foundation, either version 3 of the License, or
|
|
% (at your option) any later version.
|
|
%
|
|
% Dynare is distributed in the hope that it will be useful,
|
|
% but WITHOUT ANY WARRANTY; without even the implied warranty of
|
|
% MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
|
|
% GNU General Public License for more details.
|
|
%
|
|
% You should have received a copy of the GNU General Public License
|
|
% along with Dynare. If not, see <http://www.gnu.org/licenses/>.
|
|
%
|
|
% ------------------------------------------------
|
|
% REFERENCES: Geweke (1992), `Evaluating the accuracy of sampling-based
|
|
% approaches to the calculation of posterior moments', in J.O. Berger,
|
|
% J.M. Bernardo, A.P. Dawid, and A.F.M. Smith (eds.) Proceedings of
|
|
% the Fourth Valencia International Meeting on Bayesian Statistics,
|
|
% pp. 169-194, Oxford University Press
|
|
% Geweke (1999): `Using simulation methods for Bayesian econometric models:
|
|
% Inference, development and communication', Econometric Reviews, 18(1),
|
|
% 1-73
|
|
|
|
% written by: Johannes Pfeifer,
|
|
% based on code by James P. LeSage, who in turn
|
|
% drew on MATLAB programs written by Siddartha Chib
|
|
|
|
for k=1:length(options.convergence.geweke.taper_steps)+1
|
|
NSE=[results1(:,3+(k-1)*2) results2(:,3+(k-1)*2)];
|
|
means=[results1(:,1) results2(:,1)];
|
|
diff_Means=means(:,1)-means(:,2);
|
|
sum_of_weights=sum(1./(NSE.^2),2);
|
|
pooled_mean=sum(means./(NSE.^2),2)./sum_of_weights;
|
|
pooled_NSE=1./sqrt(sum_of_weights);
|
|
|
|
test_stat=diff_Means.^2./sum(NSE.^2,2);
|
|
p = 1-chi2cdf(test_stat,1);
|
|
results_struct.pooled_mean(:,k) = pooled_mean;
|
|
results_struct.pooled_nse(:,k) = pooled_NSE;
|
|
results_struct.prob_chi2_test(:,k) = p;
|
|
end
|