Open Access

Estimating genetic covariance functions assuming a parametric correlation structure for environmental effects

Genetics Selection Evolution200133:557

Received: 3 November 2000

Accepted: 23 April 2001

Published: 15 November 2001


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.


repeated recordsrandom regression modelcorrelation functionestimationREML

(To access the full article, please see PDF)

Authors’ Affiliations

Animal Genetics and Breeding Unit (A joint unit with NSW Agriculture), University of New England


© INRA, EDP Sciences 2001