Abstract
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 problem being that the data arise either from selection experiments or from breeders' herds which are undergoing selection. Consequently, the usual methods are likely to yield biased estimates and predictions. Methods for dealing with such data are presented in this paper.
Keywords
Best linear unbiased predictionSelection (genetic algorithm)Linear modelModel selectionComputer scienceGeneralized linear mixed modelRandom effects modelSampling (signal processing)Mixed modelStatisticsUnbiased EstimationMathematicsMathematical optimizationMachine learning
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Publication Info
- Year
- 1975
- Type
- article
- Volume
- 31
- Issue
- 2
- Pages
- 423-47
- Citations
- 709
- Access
- Closed
External Links
Citation Metrics
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Cite This
Henderson Cr
(1975).
Best linear unbiased estimation and prediction under a selection model..
PubMed
, 31
(2)
, 423-47.