Gianola D, Foulley J L, Fernando R L, Henderson C R, Weigel K A
Department of Meat and Animal Science, University of Wisconsin, Madison 53706.
J Dairy Sci. 1992 Oct;75(10):2805-23. doi: 10.3168/jds.S0022-0302(92)78044-8.
Procedures are described to estimate variances when heterogeneity of genetic and residual dispersion parameters exists for some criterion. Genetic and residual variances are considered to follow distributions with either known or unknown parameters. The estimates of variances obtained are weighted averages of the corresponding parameter and of a data-based statistic. Although the techniques presented are largely inspired by Bayesian ideas, the procedures can be given a frequentist interpretation, and the parameters of the prior distributions can be estimated from the data at hand. Techniques are described and illustrated for situations in which animals are related or unrelated across herds. We conjecture that the proposed estimators have smaller mean squared error than those obtained by grouping observations in some way and then applying REML within each group.
本文描述了在某些标准下遗传和残差离散参数存在异质性时估计方差的方法。遗传方差和残差方差被认为服从参数已知或未知的分布。所获得的方差估计值是相应参数和基于数据的统计量的加权平均值。虽然所提出的技术在很大程度上受到贝叶斯思想的启发，但这些方法可以给出一个频率主义的解释，并且先验分布的参数可以从手头的数据中估计出来。本文描述并举例说明了动物在不同畜群之间相关或不相关的情况。我们推测，与通过某种方式对观测值进行分组然后在每组内应用REML所获得的估计值相比，所提出的估计量具有更小的均方误差。
