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

<p>Abstract</p> <p>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 fact...

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Bibliographic Details
Main Authors: Van Dyk David A, Foulley Jean-Louis
Format: Article
Language:deu
Published: BMC 2000-03-01
Series:Genetics Selection Evolution
Subjects:
Online Access:http://www.gsejournal.org/content/32/2/143
Description
Summary:<p>Abstract</p> <p>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.</p>
ISSN:0999-193X
1297-9686