BAYESIAN-INFERENCE ABOUT DISPERSION PARAMETERS OF UNIVARIATE MIXED MODELS WITH MATERNAL EFFECTS - THEORETICAL CONSIDERATIONS

被引：14

作者：

CANTET, RJC ^{[1
]}

FERNANDO, RL ^{[1
]}

GIANOLA, D ^{[1
]}

机构：

[1] UNIV ILLINOIS, DEPT ANIM SCI, URBANA, IL 61801 USA

来源：

GENETICS SELECTION EVOLUTION | 1992年 / 24卷 / 02期

关键词：

MATERNAL EFFECT; BAYESIAN METHOD; DISPERSION PARAMETER;

D O I：

10.1051/gse:19920202

中图分类号：

S8 [畜牧、动物医学、狩猎、蚕、蜂];

学科分类号：

0905 ;

摘要：

Mixed linear models for maternal effects include fixed and random elements, and dispersion parameters (variances and covariances). In this paper a Bayesian model for inferences about such parameters is presented. The model includes a normal likelihood for the data, a "flat" prior for the fixed effects and a multivariate normal prior for the direct and maternal breeding values. The prior distribution for the genetic variance-covariance components is in the inverted Wishart form and the environmental components follow inverted chi-2 prior distributions. The kernel of the joint posterior density of the dispersion parameters is derived in closed form. Additional numerical and analytical methods of interest that are suggested to complete a Bayesian analysis include Monte-Carlo Integration, maximum entropy fit, asymptotic approximations, and the Tierney-Kadane approach to marginalization.

引用

页码：107 / 135

页数：29

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