代码搜索：multivariate

找到约 564 项符合「multivariate」的源代码

代码结果 564
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www.eeworm.com/read/449504/7502702

m diagonal_bekk_t_mvgarch.m

function [parameters, loglikelihood, Ht, likelihoods, stdresid, stderrors, A, B, scores] = diagonal_bekk_T_mvgarch(data,p,q,BEKKoptions); % PURPOSE: % To Estimate a diagonal BEKK multivariate G
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www.eeworm.com/read/445211/7597976

m minimize.m

function [X, fX, i] = minimize(X, f, length, varargin); % Minimize a continuous differentialble multivariate function. Starting point % is given by "X" (D by 1), and the function named in the string
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www.eeworm.com/read/441245/7672650

m gauss.m

%GAUSS Generation of a multivariate Gaussian dataset % % A = GAUSS(N,U,G,LABTYPE) % % INPUT (in case of generation a 1-class dataset in K dimensions) % N Number of objects to be generated (d
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www.eeworm.com/read/198546/7928762

m dcc_mvgarch.m

function [parameters, loglikelihood, Ht, Qt, stdresid, likelihoods, stderrors, A,B, jointscores]=dcc_mvgarch(data,dccP,dccQ,archP,garchQ) % PURPOSE: % Estimates a multivariate GARCH model us
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www.eeworm.com/read/198546/7928778

m scalar_bekk_mvgarch.m

function [parameters, loglikelihood, Ht, likelihoods, stdresid, stderrors, A, B, scores] = scalar_bekk_mvgarch(data,p,q,BEKKoptions); % PURPOSE: % To Estimate a scalar BEKK multivariate GARCH m
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www.eeworm.com/read/198546/7928783

m full_bekk_mvgarch.m

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 mod
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www.eeworm.com/read/198546/7928806

m scalar_bekk_t_mvgarch.m

function [parameters, loglikelihood, Ht, likelihoods, stdresid, stderrors, A, B, scores] = scalar_bekk_T_mvgarch(data,p,q,BEKKoptions); % PURPOSE: % To Estimate a scalar BEKK multivariate GARCH
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www.eeworm.com/read/198546/7928826

m diagonal_bekk_t_mvgarch.m

function [parameters, loglikelihood, Ht, likelihoods, stdresid, stderrors, A, B, scores] = diagonal_bekk_T_mvgarch(data,p,q,BEKKoptions); % PURPOSE: % To Estimate a diagonal BEKK multivariate G
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www.eeworm.com/read/400577/11572614

m gauss.m

%GAUSS Generation of a multivariate Gaussian dataset % % A = GAUSS(N,U,G,LABTYPE) % % INPUT (in case of generation a 1-class dataset in K dimensions) % N Number of objects to be generated (d
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www.eeworm.com/read/374411/9407223

m ksizemsp.m

function h = ksizeMSP(npd,noIQR) % "Maximal Smoothing Principle" estimate (Terrel '90) % Modified similarly to ROT for multivariate densities % Use ksizeMSP(X,1) to force use of stddev. instead of
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