Huisman A E, Veerkamp R F, van Arendonk J A M
Animal Breeding and Genetics Group, Wageningen Institute of Animal Sciences, Wageningen University, The Netherlands.
J Anim Sci. 2002 Mar;80(3):575-82. doi: 10.2527/2002.803575x.
Various random regression models have been advocated for the fitting of covariance structures. It was suggested that a spline model would fit better to weight data than a random regression model that utilizes orthogonal polynomials. The objective of this study was to investigate which kind of random regression model fits best to weight data of pigs. Two random regression models that described weight of individual pigs, one using orthogonal polynomials, and the other using splines, were compared. A comparison with a multivariate model, Akaike's information criterion, and the Bayesian-Schwarz information criterion were used to select the best model. Genetic, permanent environmental, and total variances increased with age. Heritabilities for the multivariate model ranged from 0.14 to 0.19, and for both random regression models the heritabilities were fluctuating around 0.17. Both genetic and phenotypic correlations decreased when the interval between measurements increased. The spline model needed fewer parameters than the multivariate and polynomial models. Akaike's information criterion was least for the spline model and greatest for the multivariate model. The Bayesian-Schwarz information criterion was least for the polynomial model and greatest for the multivariate model. Residuals of all models were normally distributed. Based on these results, it is concluded that random regression models provide the best fit to pig weight data.
为了拟合协方差结构，人们提倡使用各种随机回归模型。有人认为，样条模型对体重数据的拟合效果要优于使用正交多项式的随机回归模型。本研究的目的是调查哪种随机回归模型对猪的体重数据拟合效果最佳。比较了两种描述个体猪体重的随机回归模型，一种使用正交多项式，另一种使用样条。通过与多变量模型比较、赤池信息准则和贝叶斯-施瓦茨信息准则来选择最佳模型。遗传方差、永久环境方差和总方差均随年龄增长而增加。多变量模型的遗传力范围为0.14至0.19，两种随机回归模型的遗传力均在0.17左右波动。当测量间隔增加时，遗传相关性和表型相关性均降低。样条模型所需的参数比多变量模型和多项式模型少。赤池信息准则对样条模型最小，对多变量模型最大。贝叶斯-施瓦茨信息准则对多项式模型最小，对多变量模型最大。所有模型的残差均呈正态分布。基于这些结果，得出随机回归模型对猪体重数据拟合效果最佳的结论。
