The use of Bayesian statistics in animal breeding: a brief explanation.

This paper describes the study of Bayesian techniques in animal breeding, in order to discuss and clarify this approach compared to the frequentist statistical. It will be presented two algorithms for stochastic integration by Monte Carlo simulation of Markov Chains (MCMC): the Gibbs sampler and Metropolis-Hastings. It is considered the application of these techniques mentioned as an alternative to animal breeding programs in the estimation of genetic parameters in order to solve problems related to more complex models and the expression of traits of economic interest that do not have normal distribution. The proposed approaches are explained and discussed in developing of this paper.