Please use this identifier to cite or link to this item: https://une.intersearch.com.au/unejspui/handle/1959.11/891
Title: Random regression analyses using B-splines to model growth of Australian Angus Cattle
Contributor(s): Meyer, K (author)
Publication Date: 2005
Open Access: Yes
DOI: 10.1051/gse:2005012
Handle Link: https://hdl.handle.net/1959.11/891
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 cattlefrom birth to 820 days of age are presented. Data comprised 84 533 records on 20 731 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, butfluctuated 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 firsteigenfunctions 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.
Publication Type: Journal Article
Source of Publication: Genetics Selection Evolution, 37(5), p. 473-500
Publisher: INRA, EDP Sciences
Place of Publication: France
ISSN: 0999-193X
Field of Research (FOR): 070201 Animal Breeding
Peer Reviewed: Yes
HERDC Category Description: C1 Refereed Article in a Scholarly Journal
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