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Article

Better estimates of genetic covariance matrices by "bending" using penalized maximum likelihood.

Genetics - 1 Jul 2010

Meyer Karin, Kirkpatrick Mark

Abstract excerpt

Obtaining accurate estimates of the genetic covariance matrix Sigma(G) for multivariate data is a fundamental task in quantitative genetics and important for both evolutionary biologists and plant or animal breeders. Classical methods for estimating Sigma(G) are well known to suffer from substantial sampling errors; importantly, its leading eigenvalues are systematically overestimated. This article proposes a...

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Identifiers

PMID: 20442220
DOI: 10.1534/genetics.109.113381
PMCID: PMC2907195

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PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026. Manifest publication-graph-cohort-2026-09-08.1.

Source receipt: pubmed, retrieved 7 Sept 2026.

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