Utilizing Gaussian Markov Random Field Properties of Bayesian Animal Models
Article first published online: 10 OCT 2009
© 2009, The International Biometric Society
Volume 66, Issue 3, pages 763–771, September 2010
How to Cite
Steinsland, I. and Jensen, H. (2010), Utilizing Gaussian Markov Random Field Properties of Bayesian Animal Models. Biometrics, 66: 763–771. doi: 10.1111/j.1541-0420.2009.01336.x
- Issue published online: 10 OCT 2009
- Article first published online: 10 OCT 2009
- Received June 2008. Revised July 2009. Accepted July 2009.
- Additive genetic effects;
- Approximate Bayesian inference;
- Multitrait animal model;
- Quantitative genetics;
- Wild house sparrow population
Summary In this article, we demonstrate how Gaussian Markov random field properties give large computational benefits and new opportunities for the Bayesian animal model. We make inference by computing the posteriors for important quantitative genetic variables. For the single-trait animal model, a nonsampling-based approximation is presented. For the multitrait model, we set up a robust and fast Markov chain Monte Carlo algorithm. The proposed methodology was used to analyze quantitative genetic properties of morphological traits of a wild house sparrow population. Results for single- and multitrait models were compared.