tailieunhanh - báo cáo khoa học: "Empirical Bayes estimation of parameters for binary traits"

Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành y học dành cho các bạn tham khảo đề tài: Empirical Bayes estimation of parameters for binary traits | Génét. Sél. Evol. 1987 19 2 197-224 Empirical Bayes estimation of parameters for n polygenic binary traits . FOULLEY s. IM D. GIANOLA and Ina HÕSCHELE . Station de Génétique quantitative et appliquée Centre de Recherches Zootechniques F 78350 Jouy-en-Josas . Laboratoừe de Biométrie Centre de Recherches de Toulouse . 27 F 31326 Castanet-Tolosan Cedex. Department of Animal Sciences University of Illinois Urbana Illinois 61801 . Universitãt Hohenheim Institut 470 Haustiergenetik D-7000 Stuttgart 70 . Summary The conditional probability of an observation in a subpopulation i a combination of levels of explanatory variables falling into one of 2 mutually exclusive and exhaustive categories is modelled using a normal integral in n-dimensions. The mean of subpopulation i is written as a linear combination of an unknown vector 0 which can include fixed effects . nuisance environmental effects genetic group effects and random effects such as additive genetic value or producing ability. Conditionally on e the normal integral depends on an unknown matrix R comprising residual correlations in a multivariate standard normal conceptual scale. The random variables in 0 have a dispersion matrix G A where usually A is a known matrix of additive genetic relationships and G is a matrix of unknown genetic variances and covariances. It is assumed a priori that 0 follows a multivariate normal distribution f 0 I G which does not depend on R and the likelihood function is taken as product multinomial. The point estimator of 0 is the mode of the posterior distribution f 0 I Y G G R R where Y is data and G and R are the components of the mode of the marginal posterior distribution f G R I Y using flat priors for G and R. The matrices G and R correspond to the marginal maximum likelihood estimators of the corresponding matrices The point estimator of 0 is of the empirical Bayes types Overall computations involve solving 3 non-linear systems in 0 G and R. G .

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