Please use this identifier to cite or link to this item: http://hdl.handle.net/11455/37059
標題: Maximum likelihood estimation for multivariate skew normal mixture models
作者: Lin, T.I.
林宗儀
關鍵字: EM algorithm
Multivariate truncated normal distributions
Skew normal
mixtures
Stochastic representation
em algorithm
t-distribution
distributions
期刊/報告no:: Journal of Multivariate Analysis, Volume 100, Issue 2, Page(s) 257-265.
摘要: This paper provides a flexible mixture modeling framework using the multivariate skew normal distribution. A feasible EM algorithm is developed for finding the maximum likelihood estimates of parameters in this context. A general information-based method for obtaining the asymptotic covariance matrix of the maximum likelihood estimators is also presented. The proposed methodology is illustrated with a real example and results are also compared with those obtained from fitting normal Mixtures. (C) 2008 Elsevier Inc. All rights reserved.
URI: http://hdl.handle.net/11455/37059
ISSN: 0047-259X
文章連結: http://dx.doi.org/10.1016/j.jmva.2008.04.010
Appears in Collections:統計學研究所

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