NDLI: ML estimation for multivariate shock models via an EM algorithm

Content Provider	Springer Nature Link
Author	Karlis, Dimitris
Copyright Year	2003
Abstract	Multivariate extensions of univariate distributions, though useful, have not been applied in practice mainly due to shortage of inferential procedures caused by numerical complexity. The multivariate Marshall-Olkin distribution is a multivariate extension of the exponential distribution. Its representation as a multivariate shock model makes it appealing for such applications. Unfortunately, ML estimation is not easy and special numerical techniques are needed. In this paper an EM type algorithm based on the multivariate reduction technique is described. The behavior of the algorithm is examined and a numerical example is provided.
Starting Page	817
Ending Page	830
Page Count	14
File Format	PDF
ISSN	00203157
Journal	Annals of the Institute of Statistical Mathematics
Volume Number	55
Issue Number	4
e-ISSN	15729052
Language	English
Publisher	Kluwer Academic Publishers
Publisher Date	2003-01-01
Publisher Place	Dordrecht
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Multivariate reduction Marshall-Olkin distribution maximum likelihood estimation Statistics Statistics for Business/Economics/Mathematical Finance/Insurance
Content Type	Text
Resource Type	Article
Subject	Statistics and Probability

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ML estimation for multivariate shock models via an EM algorithm