Please use this identifier to cite or link to this item: https://hdl.handle.net/1959.11/14327
Title: Post-Estimation Penalization: More 'PEP' for Estimates of Genetic Covariance Matrices
Contributor(s): Meyer, Karin (author)
Publication Date: 2013
Handle Link: https://hdl.handle.net/1959.11/14327
Abstract: Maximum likelihood estimation of genetic covariances subject to a penalty to reduce sampling variation has been shown to yield improved estimates, especially for analyses comprising many traits. However, this can increase computational requirements substantially. Similarly, penalties have been found to be beneficial in a maximum likelihood based approach for pooling results from analyses of subsets of traits. This paper examines the scope for using the latter method to apply penalties to results from multivariate analyses in a computationally undemanding post-estimation step. A simulation study is presented demonstrating that even slight changes to estimates in this way can result in 'regularized' values markedly closer to population values than standard, unpenalized estimates.
Publication Type: Conference Publication
Conference Name: 20th Conference of the Association for the Advancement of Animal Breeding and Genetics: Translating Science into Action, Napier, New Zealand, 20th - 23rd October, 2013
Conference Details: 20th Conference of the Association for the Advancement of Animal Breeding and Genetics: Translating Science into Action, Napier, New Zealand, 20th - 23rd October, 2013
Source of Publication: Proceedings of the Twentieth Conference of the Association for the Advancement of Animal Breeding and Genetics, p. 424-427
Publisher: AAABG: Association for the Advancement of Animal Breeding and Genetics
Place of Publication: Palmerston North, New Zealand
Field of Research (FOR): 060499 Genetics not elsewhere classified
Peer Reviewed: Yes
HERDC Category Description: E1 Refereed Scholarly Conference Publication
Other Links: http://www.aaabg.org/aaabghome/proceedings20.php
Series Name: Proceedings of the AAABG ... Conference
Series Number : 20
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