Thompson E A, Shaw R G
Department of Statistics GN22, University of Washington, Seattle.
Biometrics. 1990 Jun;46(2):399-413.
Recent developments in the animal breeding literature facilitate estimation of the variance components in quantitative genetic models. However, computation remains intensive, and many of the procedures are restricted to specialized designs and models, unsuited to data arising from studies of natural populations. We develop algorithms that allow maximum likelihood estimation of variance components for data on arbitrary pedigree structures. The proposed methods can be implemented on microcomputers, since no intensive matrix computations or manipulations are involved. Although parts of our procedures have been previously presented, we unify these into an overall scheme whose intuitive justification clarifies the approach. Two examples are analyzed: one of data on a natural population of Salivia lyrata and the other of simulated data on an extended pedigree.
动物育种文献中的最新进展有助于估计数量遗传模型中的方差分量。然而，计算仍然很耗时，并且许多程序仅限于特殊的设计和模型，不适用于自然种群研究产生的数据。我们开发了一些算法，可对任意谱系结构的数据进行方差分量的最大似然估计。由于不涉及密集的矩阵计算或操作，因此所提出的方法可以在微型计算机上实现。虽然我们程序的部分内容之前已经介绍过，但我们将它们统一到一个整体方案中，其直观的理由阐明了该方法。分析了两个例子：一个是关于琴叶鼠尾草自然种群的数据，另一个是关于扩展谱系的模拟数据。
