期刊论文详细信息
Genetics Selection Evolution
Random regression analyses using B-splines to model growth of Australian Angus cattle
Karin Meyer1 
[1] Animal Genetics and Breeding Unit (AGBU is a joint venture between the NSW Department of Primary Industries and the University of New England.), University of New England, Armidale NSW 2351, Australia
关键词: B-splines;    random regression;    beef cattle;    growth;    covariance function;   
Others  :  1094211
DOI  :  10.1186/1297-9686-37-6-473
 received in 2004-10-04, accepted in 2005-05-02,  发布年份 2005
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【 摘 要 】

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 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.

【 授权许可】

   
2005 INRA, EDP Sciences

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