Analytic calculations for the EM algorithm for multivariate skew-t mixture models

被引：52

作者：

Vrbik, I. ^{[1
]}

McNicholas, P. D. ^{[1
]}

机构：

[1] Univ Guelph, Dept Stat, Guelph, ON N1G 2W1, Canada

来源：

STATISTICS & PROBABILITY LETTERS | 2012年 / 82卷 / 06期

关键词：

Multivariate skew-t distribution; Mixture models; EM algorithm; Skewness; MAXIMUM-LIKELIHOOD; DISTRIBUTIONS;

D O I：

10.1016/j.spl.2012.02.020

中图分类号：

O21 [概率论与数理统计]; C8 [统计学];

学科分类号：

020208 ; 070103 ; 0714 ;

摘要：

The EM algorithm can be used to compute maximum likelihood estimates of model parameters for skew-t mixture models. We show that the intractable expectations needed in the E-step can be written out analytically. These closed form expressions bypass the need for numerical estimation procedures, such as Monte Carlo methods, leading to accurate calculation of maximum likelihood estimates. Our approach is illustrated on two real data sets. (c) 2012 Elsevier B.V. All rights reserved.

引用

收藏

页码：1169 / 1174

页数：6

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