Open Access

The PX-EM algorithm for fast stable fitting of Henderson's mixed model

Genetics Selection Evolution200032:143

https://doi.org/10.1186/1297-9686-32-2-143

Received: 7 September 1999

Accepted: 3 January 2000

Published: 15 March 2000

Abstract

This paper presents procedures for implementing the PX-EM algorithm of Liu, Rubin and Wu to compute REML estimates of variance covariance components in Henderson's linear mixed models. The class of models considered encompasses several correlated random factors having the same vector length e.g., as in random regression models for longitudinal data analysis and in sire-maternal grandsire models for genetic evaluation. Numerical examples are presented to illustrate the procedures. Much better results in terms of convergence characteristics (number of iterations and time required for convergence) are obtained for PX-EM relative to the basic EM algorithm in the random regression.

Keywords

EM algorithm REML mixed models random regression variance components

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Authors’ Affiliations

(1)
Station de génétique quantitative et appliquée, Institut national de la recherche agronomique
(2)
Department of Statistics, Harvard University Cambridge

Copyright

© INRA, EDP Sciences 2000

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