title: Investigation of Gibbs sampling conditions to estimate variance components from Japanese Black carcass field data.
abstract: The genetic evaluation using the carcass field data in Japanese Black cattle has been carried out employing an animal model, implementing the restricted maximum likelihood (REML) estimation of additive genetic and residual variances. Because of rapidly increasing volumes of the official data sets and therefore larger memory spaces required, an alternative approach like the REML estimation could be useful. The purpose of this study was to investigate Gibbs sampling conditions for the single-trait variance component estimation using the carcass field data. As prior distributions, uniform and normal distributions and independent scaled inverted chi-square distributions were used for macro-environmental effects, breeding values, and the variance components, respectively. Using the data sets of different sizes, the influences of Gibbs chain length and thinning interval were investigated, after the burn-in period was determined using the coupling method. As would be expected, the chain lengths had obviously larger effects on the posterior means than those of thinning intervals. The posterior means calculated using every 10th sample from 90,000 of samples after 10,000 samples discarded as burn-in period were all considered to be reasonably comparable to the corresponding estimates by REML.
authors.affiliation: Graduate School of Science and Technology, Niigata University, Nishi, Niigata, Japan.
authors.forename: Aisaku
authors.initials: A
authors.lastname: Arakawa
authors.forename: Hiroaki
authors.initials: H
authors.lastname: Iwaisaki
authors.forename: Katsuhito
authors.initials: K
authors.lastname: Anada
mesh_terms: D000465:Algorithms; D000822:Animal Husbandry; D000818:Animals; D001947:Breeding / Q000706:statistics & numerical data*; D002417:Cattle; D003198:Computer Simulation / Q000706:statistics & numerical data*; D004777:Environment; D016013:Likelihood Functions; D008460:Meat / Q000706:statistics & numerical data*; D015233:Models, Statistical; D015999:Multivariate Analysis