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ECM Algorithm for Fitting of Mixtures of Multivariate Skew t-Distribution
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 Title & Authors
ECM Algorithm for Fitting of Mixtures of Multivariate Skew t-Distribution
Kim, Seung-Gu;
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 Abstract
Cabral et al. (2012) defined a mixture model of multivariate skew t-distributions(STMM), and proposed the use of an ECME algorithm (a variation of a standard EM algorithm) to fit the model. Their estimation by the ECME algorithm is closely related to the estimation of the degree of freedoms in the STMM. With the ECME, their purpose is to escape from the calculation of a conditional expectation that is not provided by a closed form; however, their estimates are quite unstable during the procedure of the ECME algorithm. In this paper, we provide a conditional expectation as a closed form so that it can be easily calculated; in addition, we propose to use the ECM algorithm in order to stably fit the STMM.
 Keywords
Multivariate skew t-distribution;mixture model;ECME algorithm;ECM algorithm;estimation of degree of freedom;
 Language
Korean
 Cited by
1.
Diagnosis of Observations after Fit of Multivariate Skew t-Distribution: Identification of Outliers and Edge Observations from Asymmetric Data,;

응용통계연구, 2012. vol.25. 6, pp.1019-1026 crossref(new window)
1.
Diagnosis of Observations after Fit of Multivariate Skew t-Distribution: Identification of Outliers and Edge Observations from Asymmetric Data, Korean Journal of Applied Statistics, 2012, 25, 6, 1019  crossref(new windwow)
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