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http://dx.doi.org/10.5351/KJAS.2014.27.5.819

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

Kim, Seung-Gu (Department of Data and Information, Sangji University)
Publication Information
The Korean Journal of Applied Statistics / v.27, no.5, 2014 , pp. 819-831 More about this Journal
Abstract
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.
Keywords
Multivariate skew t-distribution; mixture model; EM algorithm; AECM algorithm;
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Times Cited By KSCI : 1  (Citation Analysis)
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