TAILIEUCHUNG - báo cáo khoa học: "Prediction of breeding values when variances"

Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành y học dành cho các bạn tham khảo đề tài: Prediction of breeding values when variances | Génét. Sél. Evol. 1986 18 4 485-498 Prediction of breeding values when variances are not known D. GIANOLA . FOULLEY and . FERNANDO Department of Animal Sciences University of Illinois at Urbana Champaign . Station de Génệtique quantitative et appliquée Centre de Recherches Zootechniques F 78350 Jouy-en-Josas Summary The joint distribution of breeding values and of records usually depends on unknown parameters such as means variances and covariances in the case of the multivariate normal distribution. If the objective of the analysis is to make selection decisions these parameters should be considered as nuisances . If the values of the parameters are unknown the state of uncertainty can be represented by a prior probability distribution. This is then combined with the information contributed by the data to form a posterior distribution from which the needed predictors are calculated after integrating out the nuisances . Prediction under alternative states of knowledge is discussed in this paper and the corresponding solutions presented. It is shown that when the dispersion structure is unknown modal estimators of variance parameters should be considered. Because a Bayesian framework is adopted the estimates so obtained are necessarily non-negative. If prior knowledge about means and variances is completely vague and the distribution is multivariate normal the optimal predictors in the sense of maximizing the expected merit of the selected candidates can be approximated by using the mixed model equations with the unknown variances replaced by restricted maximum likelihood estimates. This leads to empirical Bayes predictors of breeding values. Key words Bayesian inference BLUP prediction breeding values. Resume Prediction des valeurs génétiques avec variances inconnues La distribution conjointe des valeurs génétiques et des performances depend habituellement de paramètres inconnus tels que les esperances les variances et covariances dans le cas de

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