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2024年4月16日发(作者:input函数怎么用python)

BEKK—GARCH模型之Matlab编程

function [parameters, loglikelihood, Ht, likelihoods, stdresid, stderrors,

A, B, scores] = full_bekk_mvgarch(data,p,q, BEKKoptions)

% PURPOSE:

% To Estimate a full BEKK multivariate GARCH model. ****SEE WARNING AT

END OF HELP FILE****

%

%

% USAGE:

% [parameters, loglikelihood, Ht, likelihoods, stdresid, stderrors, A, B,

scores] = full_bekk_mvgarch(data,p,q,options);

%

% INPUTS:

% data - A t by k matrix of zero mean residuals

% p - The lag length of the innovation process

% q - The lag length of the AR process

% options — (optional) Options for the optimization(fminunc)

%

% OUTPUTS:

% parameters - A (k*(k+1))/2+p*k^2+q*k^2 vector of estimated

parameteters。

% For any k^2 set of Innovation or AR parameters X,

% reshape(X,k,k) will give the correct matrix

% To recover C, use ivech(parmaeters(1:(k*(k+1))/2)

% loglikelihood — The loglikelihood of the function at the optimum

% Ht - A k x k x t 3 dimension matrix of conditional covariances

% likelihoods — A t by 1 vector of individual likelihoods

% stdresid — A t by k matrix of multivariate standardized residuals


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