Work

A note on bias in reduced rank estimates of covariance matrices

Year: 2007

Type: conference-paper

Abstract: Fitting only the leading principal components allows genetic covariance matrices to be modelled parsimoniously, yielding reduced rank estimates. If principal components with non-zero variances are omitted from the model, genetic variation is moved into the covariance matrices for residuals or other random effects. The resulting bias in estimates of genetic eigen-values and -vectors is examined.

Source: RUNE (Research UNE)

Authors: Karin Meyer, Mark Kirkpatrick

Language: English

Topic: Genetic and phenotypic traits in livestock

Subfield: Genetics

Field: Biochemistry, Genetics and Molecular Biology

Domain: Life Sciences

Open Access status: green

Funders: National Science Foundation, Meat and Livestock Australia

OpenAlex ID: W360847989

FWCI: 7.014

Cites:

Cited by: 4

Related to: 10