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Оценка баранов-производителей методом BLUP Sm
Сборник научных трудов Ставропольского научно-исследовательского института животноводства и кормопроизводства, 2013 openaire +1 more source
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Agronomy Journal, 2023
AbstractThe early stages of wheat breeding programs often contain large number of plants in segregating populations that must be selected. Selecting the best populations and plants in those stages is not an easy task, making it necessary to use robust methodologies that facilitate the selection process. The goals of this work were to evaluate different
Caique Machado e Silva +4 more
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AbstractThe early stages of wheat breeding programs often contain large number of plants in segregating populations that must be selected. Selecting the best populations and plants in those stages is not an easy task, making it necessary to use robust methodologies that facilitate the selection process. The goals of this work were to evaluate different
Caique Machado e Silva +4 more
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Agronomy Journal, 2019
3 Supplemental R codes 14 3.1 Predictive accuracy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14 3.1.1 Printing the means of RMSPD estimates . . . . . . . . . . . . . . . . 15 3.1.2 Plotting the RMSPD estimates . . . . . . . . . . . .
Tiago Olivoto +5 more
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3 Supplemental R codes 14 3.1 Predictive accuracy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14 3.1.1 Printing the means of RMSPD estimates . . . . . . . . . . . . . . . . 15 3.1.2 Plotting the RMSPD estimates . . . . . . . . . . . .
Tiago Olivoto +5 more
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2020
Recall from Sect. 13.5 that E-BLUP, the conventional procedure for predicting a predictable linear function τ = cTβ + u under the prediction-extended general mixed linear model $$\displaystyle \left \{\left (\begin {array}{c}\mathbf {y} \\ u\end {array}\right ),\left (\begin {array}{c}\mathbf { X}\boldsymbol {\beta } \\ 0 \end {array}\right ),\left
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Recall from Sect. 13.5 that E-BLUP, the conventional procedure for predicting a predictable linear function τ = cTβ + u under the prediction-extended general mixed linear model $$\displaystyle \left \{\left (\begin {array}{c}\mathbf {y} \\ u\end {array}\right ),\left (\begin {array}{c}\mathbf { X}\boldsymbol {\beta } \\ 0 \end {array}\right ),\left
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Restricted BLUP for Mixed Linear Models
Biometrical Journal, 1991AbstractA new estimation procedure for mixed regression models is introduced. It is a development of Henderson's best linear unbiased prediction procedure which uses the joint distribution of the observed dependent random variables and the unknown realisations of the random components of the model.
C. A. McGilchrist, C. W. Aisbett
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1979
Wells gave The Bulpington of Blup the sub-title ‘Adventures, Poses, Stresses, Conflicts, and Disaster in a Contemporary Brain’. This phrase aptly describes what the novel is: a sustained and remarkably consistent study of an acutely divided individuality. Robert Bloom, in his perceptive study Anatomies of Egotism,49 has pointed out that the novel is in
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Wells gave The Bulpington of Blup the sub-title ‘Adventures, Poses, Stresses, Conflicts, and Disaster in a Contemporary Brain’. This phrase aptly describes what the novel is: a sustained and remarkably consistent study of an acutely divided individuality. Robert Bloom, in his perceptive study Anatomies of Egotism,49 has pointed out that the novel is in
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𝒟-BLUP: a differentiable genomic BLUP model with learnable variance and marker weights
1. Abstract Genomic best linear unbiased prediction (GBLUP) is widely used for genomic selection in livestock and crop breeding. There is growing interest in connecting machine learning with genomic breeding value prediction.Joseph Guhlin, Peter Dearden
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A derivation of BLUP—Best linear unbiased predictor
Statistics & Probability Letters, 1997zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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