TAILIEUCHUNG - báo cáo khoa học: "Best linear unbiased prediction when error vector is correlated with other random vectors in the model"

Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành y học dành cho các bạn tham khảo đề tài: Best linear unbiased prediction when error vector is correlated with other random vectors in the model | Génét. Sél. Evol. 1983 15 3 395-400 Best linear unbiased prediction when error vector is correlated with other random vectors in the model . SCHAEFFER and . HENDERSON Department of Animal and Poultry Science University of Guelph Guelph Ontario NIG 2WI Canada Department of Animal Science Cornell University Ithaca New York 14850 USA Summary Non-zero covariances between random factors of a linear model with the residual or error vector can be handled with best linear unbiased prediction techniques. An equivalent model for describing y in which the covariances between random vectors with residual vectors are zero is the key to the solution. Computational difficulties depend on the structure of the covariance matrix. An example is used to illustrate the calculations. Key-words linear prediction correlated vectors. Resume Meilleure prediction linéaire sans biais lorsque le vecteur d erreurs est corrélé aux autres effets aléatoires du modèle On peut trailer le cas de covariances non nulles entre d une part les facteurs aléatoires d un modèle linéaire et d autre part le vecteur des résidus en utilisant les techniques du BLUP. La clé du problème reside dans récriture d un modèle equivalent décrivant les données y de sorte que les covariances entre les vecteurs des effets aléatoires et des effets résiduels soient nulles. Les difficultes de calcul sont liées à la structure de la rratrice de covariances entre ces deux types d effets. Un exemple est donné qui illustre ces considerations. Mots-clés Prediction linéaire vecteurs corrélés. I. Introduction In mixed linear models the covariances among the residual or error vector with other random factors in the model are assumed to be zero. This assumption is ordinarily applied to most practical applications in the biological sciences when the assumption is invalid. Henderson 1975 presented best linear unbiased prediction BLUP of random elements for a general linear model and also under a selection model. The objective of this

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