The EM algorithm for graphical association models with missing data

Steffen L. Lauritzen

doi:10.1016/0167-9473(93)E0056-A

The EM algorithm for graphical association models with missing data

474 Citationer (Scopus)

Abstract

It is shown how the computational scheme of Lauritzen and Spiegelhalter (1988) can be exploited to perform the E-step of the EM algorithm when applied to finding maximum likelihood estimates or penalized maximum likelihood estimates in hierarchical log-linear models and recursive models for contingency tables with missing data. The generalization to mixed association models introduced in Lauritzen and Wermuth (1989) and Edwards (1990) is indicated.

Originalsprog	Engelsk
Tidsskrift	Computational Statistics & Data Analysis
Vol/bind	19
Udgave nummer	2
Sider (fra-til)	191-201
Antal sider	11
ISSN	0167-9473
DOI	https://doi.org/10.1016/0167-9473(93)E0056-A
Status	Udgivet - 1995
Udgivet eksternt	Ja

Adgang til dokumentet

10.1016/0167-9473(93)E0056-A

Citationsformater

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AB - It is shown how the computational scheme of Lauritzen and Spiegelhalter (1988) can be exploited to perform the E-step of the EM algorithm when applied to finding maximum likelihood estimates or penalized maximum likelihood estimates in hierarchical log-linear models and recursive models for contingency tables with missing data. The generalization to mixed association models introduced in Lauritzen and Wermuth (1989) and Edwards (1990) is indicated.

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DO - 10.1016/0167-9473(93)E0056-A

M3 - Journal article

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