Comparison of Index Selection and Best Linear Unbiased Prediction for Simulated Layer Poultry Data
نویسندگان
چکیده
منابع مشابه
Best linear unbiased estimation and prediction under a selection model.
Mixed linear models are assumed in most animal breeding applications. Convenient methods for computing BLUE of the estimable linear functions of the fixed elements of the model and for computing best linear unbiased predictions of the random elements of the model have been available. Most data available to animal breeders, however, do not meet the usual requirements of random sampling, the prob...
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Most of the available results on optimal block designs for diallel crosses are based on standard linear model assumptions where the general combining ability effects are taken as fixed. In many practical situations, this assumption may not be tenable since often one studies only a sample of inbred lines from a possibly large (hypothetical) population. Recently Ghosh and Das (2003) proposed a ra...
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Introduction Genetic progress in traits of economic importance has been impressive during the past few decades. This has been due to a combination of (1) selection, primarily on additive genetic merit, (2) changes in breed structure, and (3) crossbreeding; the relative importance of these factors varying from species to species. This paper is concerned with the first of these factors and is res...
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where X is a known n × p model matrix, the vector y is an observable ndimensional random vector, β is a p × 1 vector of unknown parameters, and ε is an unobservable vector of random errors with expectation E(ε) = 0, and covariance matrix cov(ε) = σV, where σ > 0 is an unknown constant. The nonnegative definite (possibly singular) matrix V is known. In our considerations σ has no role and hence ...
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ژورنال
عنوان ژورنال: Poultry Science
سال: 1995
ISSN: 0032-5791
DOI: 10.3382/ps.0741566