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  • Karin Meyer
  • Journal of Zhejiang University SCIENCE B
  • 2007
WOMBAT is a software package for quantitative genetic analyses of continuous traits, fitting a linear, mixed model; estimates of covariance components and the resulting genetic parameters are obtained by restricted maximum likelihood. A wide range of models, comprising numerous traits, multiple fixed and random effects, selected genetic covariance(More)
A method is described to estimate genetic and environmental covariance functions for traits measured repeatedly per individual along some continuous scale, such as time, directly from the data by Restricted Maximum Likelihood. It relies on the equivalence of a covariance function and a random regression model. By regressing on random, orthogonal polynomials(More)
Weight records of Brazilian Nelore cattle, from birth to 630 d of age, recorded every 3 mo, were analyzed using random regression models. Independent variables were Legendre polynomials of age at recording. The model of analysis included contemporary groups as fixed effects and age of dam as a linear and quadratic covariable. Mean trends were modeled(More)
  • K Meyer
  • Genetics Selection Evolution
  • 1988
A method is described for the simultaneous estimation of variance components due to several genetic and environmental effects from unbalanced data by restricted maximum likelihood (REML). Estimates are obtained by evaluating the likelihood explicitly and using standard, derivative-free optimization procedures to locate its maximum. The model of analysis(More)
  • K Meyer
  • Genetics Selection Evolution
  • 1992
The sampling behaviour of Restricted Maximum Likelihood estimates of (co)variance components due to additive genetic and environmental maternal effects is examined for balanced data with different family structures. It is shown that sampling correlations between estimates are high and that sizeable data sets are required to allow reasonably accurate(More)
Records for birth and subsequent, monthly weights until weaning on beef calves of two breeds in a selection experiment were analysed fitting random regression models. Independent variables were orthogonal (Legendre) polynomials of age at weighing in days. Orders of polynomial fit up to 6 were considered. Analyses were carried out fitting sets of random(More)
Regression on the basis function of B-splines has been advocated as an alternative to orthogonal polynomials in random regression analyses. Basic theory of splines in mixed model analyses is reviewed, and estimates from analyses of weights of Australian Angus cattle from birth to 820 days of age are presented. Data comprised 84 533 records on 20 731 animals(More)
Estimating the genetic and environmental variances for multivariate and function-valued phenotypes poses problems for estimation and interpretation. Even when the phenotype of interest has a large number of dimensions, most variation is typically associated with a small number of principal components (eigen-vectors or eigenfunctions). We propose an approach(More)
In animal breeding, knowledge of the genetic properties of the traits we are interested in is the first prerequisite in establishing a selection programme. Unless we are concerned with traits controlled by single or few genes, in which case we are generally more interested in gene frequencies, estimation of genetic parameters is synonymous with the(More)