Abstract
This paper deals with Bayesian inferences of animal models using Gibbs sampling. First, we suggest a general and efficient method for updating additive genetic effects, in which the computational cost is independent of the pedigree depth and increases linearly only with the size of the pedigree. Second, we show how this approach can be used to draw inferences from a wide range of animal models using the computer package Winbugs. Finally, we illustrate the approach in a simulation study, in which the data are generated and analyzed using Winbugs according to a linear model with i.i.d errors having Student's t distributions. In conclusion, Winbugs can be used to make inferences in small-sized, quantitative, genetic data sets applying a wide range of animal models that are not yet standard in the animal breeding literature
| Original language | English |
|---|---|
| Journal | Journal of Animal Science |
| Issue | 85 |
| Pages (from-to) | 1363-1368 |
| Number of pages | 6 |
| ISSN | 0021-8812 |
| DOIs | |
| Publication status | Published - 2007 |
Keywords
- Bayesian inference
- Winbugs
- Genetics