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

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...

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Bibliographic Details
Published inGenetics selection evolution (Paris) Vol. 32; no. 2; pp. 143 - 163
Main Authors Foulley, Jean-Louis, Van Dyk, David A
Format Journal Article
LanguageEnglish
Published France BioMed Central Ltd 15.03.2000
Springer Nature B.V
BioMed Central
BMC
Subjects
Algorithms
Basic converters
Convergence
Data analysis
EM algorithm
Genetic algorithms
Genetic variation
Genetics
Life Sciences
mixed models
random regression
Regression analysis
Regression models
REML
variance components
France
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ISSN1297-9686
0999-193X
1297-9686
DOI10.1186/1297-9686-32-2-143

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Summary: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.
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ISSN:1297-9686
0999-193X
1297-9686
DOI:10.1186/1297-9686-32-2-143