An Alternating Approach of Maximum Likelihood Estimation for Mixture of Multivariate Skew t-Distribution

被引：1
|
作者：
Kim, Seung-Gu [1 ]
机构：
[1] Sangji Univ, Dept Data & Informat, Wonju 220702, South Korea
来源：
KOREAN JOURNAL OF APPLIED STATISTICS | 2014年 / 27卷 / 05期
关键词：
Multivariate skew t-distribution; mixture model; EM algorithm; AECM algorithm;
D O I：
10.5351/KJAS.2014.27.5.819
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 Exact-EM algorithm can conventionally fit a mixture of multivariate skew distribution. However, it suffers from highly expensive computational costs to calculate the moments of multivariate truncated t-distribution in E-step. This paper proposes a new SPU-EM method that adopts the AECM algorithm principle proposed by Meng and van Dyk (1997)'s to circumvent the multi-dimensionality of the moments. This method offers a shorter execution time than a conventional Exact-EM algorithm. Some experments are provided to show its effectiveness.
引用
收藏
页码：819 / 831
页数：13
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