ESTIMATING VARIANCES AND COVARIANCES FOR MULTIVARIATE ANIMAL-MODELS BY RESTRICTED MAXIMUM-LIKELIHOOD
ESTIMATING VARIANCES AND COVARIANCES FOR MULTIVARIATE ANIMAL-MODELS BY RESTRICTED MAXIMUM-LIKELIHOOD
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DOI：
10.1051/gse:19910106
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发表时间：
1991-01-01
影响因子：
4.1
通讯作者：
MEYER, K
中科院分区：
文献类型：
--
作者：
MEYER, K
方差和协方差分量的受限最大似然估计可以通过使用标准的无导数优化程序直接最大化相关的似然来获得。 一般来说，这需要多维搜索和（对数）似然函数的大量评估。 在单变量情况下，已描述了在动物模型下使用该方法进行分析。 该模型将动物的加性遗传价值作为随机效应，并考虑了动物之间的所有关系。 此外，其他随机因素，如共同的环境或母体遗传效应也可以拟合。 本文介绍了扩展到多变量分析，允许丢失的记录。 给出了一个数值例子，并讨论了具体模型的简化。
Restricted maximum likelihood estimates of variance and covariance components can be obtained by direct maximization of the associated likelihood using standard, derivative-free optimization procedures. In general, this requires a multi-dimensional search and numerous evaluations of the (log) likelihood function. Use of this approach for analyses under an animal model has been described for the univariate case. This model includes animals' additive genetic merit as random effect and accounts for all relationships between animals. In addition, other random factors such as common environmental or maternal genetic effects can be fitted. This paper describes the extension to multivariate analyses, allowing for missing records. A numerical example is given and simplifications for specific models are discussed.