Issue |
Genet. Sel. Evol.
Volume 37, Number 5, September-October 2005
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|
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Page(s) | 473 - 500 | |
DOI | https://doi.org/10.1051/gse:2005012 |
DOI: 10.1051/gse:2005012
Random regression analyses using B-splines to model growth of Australian Angus cattle
Karin MeyerAnimal Genetics and Breeding Unit, University of New England, Armidale NSW 2351, Australia
(Received 4 October 2004; accepted 2 May 2005)
Abstract -
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
records on
animals in 43 herds, with a high proportion of
animals with 4 or more weights recorded. Changes in weights with age
were modelled through B-splines of age at recording. A total of
thirteen analyses, considering different combinations of linear,
quadratic and cubic B-splines and up to six knots, were carried out.
Results showed good agreement for all ages with many records, but
fluctuated where data were sparse. On the whole, analyses using
B-splines appeared more robust against "end-of-range" problems and
yielded more consistent and accurate estimates of the first
eigenfunctions than previous, polynomial analyses. A model fitting
quadratic B-splines, with knots at 0, 200, 400, 600 and 821 days and a
total of 91 covariance components, appeared to be a good compromise
between detailedness of the model, number of parameters to be
estimated, plausibility of results, and fit, measured as residual mean
square error.
Key words: covariance function / growth / beef cattle / random regression / B-splines
Correspondence and reprints: kmeyer@didgeridoo.une.edu.au
© INRA, EDP Sciences 2005