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.
| Original language | English |
|---|---|
| Title of host publication | Proceedings of the Seventeenth Conference for the Advancement of Animal Breeding and Genetics |
| Editors | AAABG: Association for the Advancement of Animal Breeding, Genetics |
| Place of Publication | Armidale, Australia |
| Publisher | Association for the Advancement of Animal Breeding and Genetics (AAABG) |
| Pages | 154-157 |
| Volume | 17 |
| ISBN (Print) | 1921208139 |
| Publication status | Published - 2007 |
| Event | AAABG 2007: 17th Conference of the Association for the Advancement of Animal Breeding and Genetics - University of New England, Armidale, Australia Duration: 23 Sept 2007 → 26 Sept 2007 |
Conference
| Conference | AAABG 2007: 17th Conference of the Association for the Advancement of Animal Breeding and Genetics |
|---|---|
| City | Armidale, Australia |
| Period | 23/09/07 → 26/09/07 |
Keywords
- Quantitative Genetics (incl Disease and Trait Mapping Genetics)
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