A Monte-Carlo algorithm for maximum likelihood estimation of variance components

被引：1

作者：

Xu, S ^{[1
]}

Atchley, WR ^{[1
]}

机构：

[1] N CAROLINA STATE UNIV,DEPT GENET,RALEIGH,NC 27695

来源：

GENETICS SELECTION EVOLUTION | 1996年 / 28卷 / 04期

基金：

美国国家科学基金会; 美国国家卫生研究院;

关键词：

maximum likelihood; restricted maximum likelihood; variance component; Monte-Carlo; mixed model;

D O I：

10.1051/gse:19960402

中图分类号：

S8 [畜牧、动物医学、狩猎、蚕、蜂];

学科分类号：

0905 ;

摘要：

A new algorithm for finding maximum likelihood (ML) solutions to variance components is introduced. This algorithm first treats random effects as fixed, then expresses the pseudo-fixed effects as linear transformations of a set of standard normal deviates which eventually are integrated out numerically through Monte-Carlo simulation. An iterative algorithm is employed to estimate the standard deviation (rather than the variance) of the random effects. This method is conceptually simple and easy to program because repeated updating and inverting the variance-covariance matrix of data is not required. It is potentially useful for handling large data sets and data that are not normally distributed.

引用

页码：329 / 343

页数：15

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