Literature DB >> 1174616

Best linear unbiased estimation and prediction under a selection model.

C R Henderson.   

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.

Mesh:

Year:  1975        PMID: 1174616

Source DB:  PubMed          Journal:  Biometrics        ISSN: 0006-341X            Impact factor:   2.571


  336 in total

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Review 2.  Estimating genetic parameters in natural populations using the "animal model".

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5.  Allelic variation in cell wall candidate genes affecting solid wood properties in natural populations and land races of Pinus radiata.

Authors:  S K Dillon; M Nolan; W Li; C Bell; H X Wu; S G Southerton
Journal:  Genetics       Date:  2010-05-24       Impact factor: 4.562

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7.  Modeling Epistasis in Genomic Selection.

Authors:  Yong Jiang; Jochen C Reif
Journal:  Genetics       Date:  2015-07-27       Impact factor: 4.562

8.  Genomic selection in a commercial winter wheat population.

Authors:  Sang He; Albert Wilhelm Schulthess; Vilson Mirdita; Yusheng Zhao; Viktor Korzun; Reiner Bothe; Erhard Ebmeyer; Jochen C Reif; Yong Jiang
Journal:  Theor Appl Genet       Date:  2016-01-08       Impact factor: 5.699

9.  Genetic and agronomic assessment of cob traits in corn under low and normal nitrogen management conditions.

Authors:  Constantin Jansen; Yongzhong Zhang; Hongjun Liu; Pedro J Gonzalez-Portilla; Nick Lauter; Bharath Kumar; Ignacio Trucillo-Silva; Juan Pablo San Martin; Michael Lee; Kevin Simcox; Jeff Schussler; Kanwarpal Dhugga; Thomas Lübberstedt
Journal:  Theor Appl Genet       Date:  2015-03-12       Impact factor: 5.699

10.  Genomic selection prediction accuracy in a perennial crop: case study of oil palm (Elaeis guineensis Jacq.).

Authors:  David Cros; Marie Denis; Leopoldo Sánchez; Benoit Cochard; Albert Flori; Tristan Durand-Gasselin; Bruno Nouy; Alphonse Omoré; Virginie Pomiès; Virginie Riou; Edyana Suryana; Jean-Marc Bouvet
Journal:  Theor Appl Genet       Date:  2014-12-07       Impact factor: 5.699

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