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Related Experiment Videos

Estimation of heterogeneous within-herd variance components using empirical Bayes methods: a simulation study.

K A Weigel1, D Gianola

  • 1Department of Dairy Science, University of Wisconsin, Madison 53706.

Journal of Dairy Science
|October 1, 1992
PubMed
Summary

Empirical Bayes methods improve genetic evaluations by combining within-herd and across-herd variance estimates. This approach enhances the accuracy of sire variance estimates and breeding values, especially with heterogeneous variances.

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Area of Science:

  • Animal Genetics
  • Quantitative Genetics
  • Statistical Genetics

Background:

  • Genetic evaluations using Best Linear Unbiased Prediction (BLUP) can handle heterogeneous variances if components are known.
  • Estimating variance components within each heterogeneous subclass is often necessary.
  • Empirical Bayes (EB) methods offer a way to combine within-herd and prior variance estimates.

Purpose of the Study:

  • To examine the properties of sire and residual variance estimates using an EB approach.
  • To assess the impact of EB methods on the accuracy of breeding values in the presence of heterogeneous variances.
  • To evaluate the convergence and accuracy of variance component estimation.

Main Methods:

  • Simulation study to evaluate EB variance component estimation.

Related Experiment Videos

  • Used Restricted Maximum Likelihood (REML) for across-herd prior estimates assuming homogeneous variances.
  • Combined within-herd and prior REML estimates using an EB approach.

    • Main Results:

    • EB improved convergence in within-herd variance component estimation where REML failed.
    • Sire variance estimates were most accurate when both within-herd and prior information were used.
    • Correlations between true transmitting abilities and predicted transmitting abilities (PTA) improved with EB estimates.
    • Selection proportions of sires became more uniform across environments with differing variances.

    Conclusions:

    • Useful variance component estimates can be obtained within herds using EB methods with across-herd estimates as prior information.
    • EB methods allow for breeding value predictions that are less influenced by heterogeneous variances.
    • This approach enhances the reliability of genetic evaluations in diverse environments.