BAYESIAN-INFERENCE ON VARIANCE AND COVARIANCE COMPONENTS FOR TRAITS INFLUENCED BY MATERNAL AND DIRECT GENETIC-EFFECTS, USING THE GIBBS SAMPLER

被引：51

作者：

JENSEN, J

WANG, CS

SORENSEN, DA

GIANOLA, D

机构：

[1] CORNELL UNIV, DEPT ANIM SCI, ITHACA, NY 14853 USA

[2] UNIV WISCONSIN, DEPT MEAT & ANIM SCI, MADISON, WI 53706 USA

来源：

ACTA AGRICULTURAE SCANDINAVICA SECTION A-ANIMAL SCIENCE | 1994年 / 44卷 / 04期

关键词：

MATERNAL EFFECTS; SHEEP; MARGINAL INFERENCE; BAYESIAN ANALYSIS;

D O I：

10.1080/09064709409410898

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 method for analyzing traits influenced by both maternal and direct genetic effects is presented in a Bayesian setting. A Bayesian analysis requires full marginalization of the joint posterior density. The necessary multidimensional integrations were carried out using the Gibbs sampler. This gives the possibility of exact marginal inference on (co)variance components of interest as opposed to results of REML analysis, where only joint inferences are possible. The method is illustrated by an example on growth in sheep.

引用

页码：193 / 201

页数：9

共 35 条

[21] RESTRICTED MAXIMUM-LIKELIHOOD TO ESTIMATE VARIANCE-COMPONENTS FOR ANIMAL-MODELS WITH SEVERAL RANDOM EFFECTS USING A DERIVATIVE-FREE ALGORITHM [J].