Issue |
Genet. Sel. Evol.
Volume 33, Number 6, November-December 2001
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|
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Page(s) | 557 - 585 | |
DOI | https://doi.org/10.1051/gse:2001102 |
Genet. Sel. Evol. 33 (2001) 557-585
Estimating genetic covariance functions assuming a parametric correlation structure for environmental effects
Karin MeyerAnimal Genetics and Breeding Unit, University of New England, Armidale NSW 2351, Australia
(Received 3 November 2000; accepted 23 April 2001)
Abstract
A random regression model for the analysis of "repeated " records in
animal breeding is described which combines a random regression
approach for additive genetic and other random effects with the
assumption of a parametric correlation structure for within animal
covariances. Both stationary and non-stationary correlation models
involving a small number of parameters are considered. Heterogeneity
in within animal variances is modelled through polynomial variance
functions. Estimation of parameters describing the dispersion
structure of such model by restricted maximum likelihood via an
"average information" algorithm is outlined. An application to mature
weight records of beef cow is given, and results are contrasted to
those from analyses fitting sets of random regression coefficients for
permanent environmental effects.
Key words: repeated records / random regression model / correlation function / estimation / REML
Correspondence and reprints: Karin Meyer
e-mail: kmeyer@didgeridoo.une.edu.au
© INRA, EDP Sciences 2001