An integrated approach to empirical Bayesian whole genome prediction modeling

DOI10.1007/s13253-015-0224-3zbMath1329.62442OpenAlexW1815679535WikidataQ59281375 ScholiaQ59281375MaRDI QIDQ906069

N. E. Zubov

Publication date: 29 January 2016

Published in: Journal of Agricultural, Biological, and Environmental Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s13253-015-0224-3

zbMATH Keywords

hierarchical Bayesiancomputational efficiencyexpectation-maximizationvariance component estimationgenomic prediction

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Bayesian inference (62F15) Protein sequences, DNA sequences (92D20) Analysis of variance and covariance (ANOVA) (62J10)

Related Items (2)

Statistical and computational challenges in whole genome prediction and genome-wide association analyses for plant and animal breeding ⋮ An approximate Bayesian significance test for genomic evaluations

Uses Software

• R
• hypred
• EMVS

Cites Work

• Unnamed Item
• That BLUP is a good thing: The estimation of random effects. With comments and a rejoinder by the author
• Maximum Likelihood Approaches to Variance Component Estimation and to Related Problems
• Average Information REML: An Efficient Algorithm for Variance Parameter Estimation in Linear Mixed Models
• Bayesian inference for variance components using only error contrasts
• EMVS: The EM Approach to Bayesian Variable Selection
• An Empirical Bayes Method for Estimating Epistatic Effects of Quantitative Trait Loci
• Prior distributions for variance parameters in hierarchical models (Comment on article by Browne and Draper)

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