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

Genetics Selection Evolution

David A Van Dyk²  Jean-Louis Foulley¹ 

[1] Station de génétique quantitative et appliquée Institut national de la recherche agronomique 78352 Jouy-en-Josas Cedex, France;Department of Statistics, Harvard University Cambridge, MA 02138, USA

关键词: variance components;    random regression;    mixed models;    REML;    EM algorithm;   

Others  :  1094828
DOI  :  10.1186/1297-9686-32-2-143

 received in 1999-09-07, accepted in 2000-01-03,  发布年份 2000

【 摘 要 】

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.

【 授权许可】

   
2000 INRA, EDP Sciences