📄 maxfilter_likelihood.m
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function [LLF, errors, likelihoods] = armaxfilter_likelihood(parameters , regressand , regressors, ma)
% PURPOSE:
% Likelihood function for armaxfilter
%
% USAGE:
% [LLF, errors, likelihoods] = armaxfilter_likelihood(parameters , regressand , regressors, ma)
%
% INPUTS:
% parameters: A vector of GARCH process aprams of the form [constant, arch, garch]
% regressand: A set of zero mean residuals
% regressors: A matrix of exogenous(conditionally) of size (1+nlags+numX) by t with a ci
% ma: The MA order of the ARMA process
%
% OUTPUTS:
% LLF: Minus 1 times the log likelihood
% errors: Time series of errors
% likelihoods: Time series of log likelihoods
%
%
% COMMENTS:
% This is a helper function for mafilter
%
% Author: Kevin Sheppard
% kksheppard@ucsd.edu
% Revision: 2 Date: 12/31/2001
tau=length(regressand);
if nargin>2 & ~isempty(regressors)
regressand=regressand-parameters(1:size(regressors,2))*regressors;
[e,E]=maxcore(regressand,parameters(size(regressors,2)+1:length(parameters)),ma,tau);
else
[e,E]=maxcore(regressand,parameters,ma,tau);
end
t = (ma + 1):tau;
sigma2=(E)/(tau-length(parameters));
LLF = 0.5*(tau*(log(sigma2)) + (E/sigma2) + tau*log(2*pi));
if nargout>1
errors=e(t);
likelihoods = (log(sigma2)) + ((errors.^2)./sigma2);
likelihoods = -0.5 * (likelihoods + log(2*pi));
end
if isnan(LLF)
LLF=1e7;
end
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