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ML Estimation of the MultivariatetDistribution and the EM Algorithm

โœ Scribed by Chuanhai Liu

Publisher
Elsevier Science
Year
1997
Tongue
English
Weight
325 KB
Volume
63
Category
Article
ISSN
0047-259X

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โœฆ Synopsis

Maximum likelihood estimation of the multivariate t distribution, especially with unknown degrees of freedom, has been an interesting topic in the development of the EM algorithm. After a brief review of the EM algorithm and its application to finding the maximum likelihood estimates of the parameters of the t distribution, this paper provides new versions of the ECME algorithm for maximum likelihood estimation of the multivariate t distribution from data with possibly missing values. The results show that the new versions of the ECME algorithm converge faster than the previous procedures. Most important, the idea of this new implementation is quite general and useful for the development of the EM algorithm. Comparisons of different methods based on two datasets are presented.

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