Making decisions about the optimal selection environment using Gibbs sampling

The use of Gibbs sampling in making decisions about the optimal selection e nvironment was demonstrated. Marginal posterior distributions of the effici ency of selection across sites were obtained using the Gibbs sampler, a Bay esian method, from which the probability that the efficiency of selection l ay between specified values and the variance of the distribution were compu ted, providing a lot of information on which to make decisions regarding th e location of genetic tests. The heritability, genetic correlations and eff iciencies of selection estimated using REML and Gibbs sampling were similar . However, the latter approach showed that the point estimates of the effic iencies of selection were subject to substantial error. The decision regard ing selection at maturity was consistent with that obtained using point est imates from REML, but Gibbs sampling allowed the efficiencies of selection to be interpreted with more confidence. The decision regarding early select ion differed from that based on REML point estimates. Generally, the decisi ons to make early selections at site B for planting at both site B and A, a nd to make selections at maturity at each individual site, were robust to d ifferent priors in the Gibbs sampling.