Abstract
Multivariate estimation fitting a common structure to estimates of genetic and environmental covariance matrices is examined in a simple simulation study. It is shown that such parsimonious estimation can considerably reduce sampling variation. However, if the assumption of similarity in structure does not hold at least approximately, bias in estimates of the genetic covariance matrix can be substantial. For small samples and more than a few traits, structured estimation is likely to reduce mean square error even if bias is quite large. Hence such models should be used cautiously.
| Original language | English |
|---|---|
| Title of host publication | Proceedings of the Association for the Advancement of Animal Breeding and Genetics |
| Editors | Alex Safari, Bill Pattie, Barrie Restall |
| Place of Publication | Armidale, Australia |
| Publisher | Association for the Advancement of Animal Breeding and Genetics (AAABG) |
| Pages | 438-441 |
| Volume | 18 |
| ISBN (Print) | 9780646521039 |
| Publication status | Published - 2009 |
| Event | AAABG 2009: 18th Conference of the Association for the Advancement of Animal Breeding and Genetics - Barossa Valley, Australia Duration: 27 Sept 2009 → 2 Oct 2009 |
Conference
| Conference | AAABG 2009: 18th Conference of the Association for the Advancement of Animal Breeding and Genetics |
|---|---|
| City | Barossa Valley, Australia |
| Period | 27/09/09 → 2/10/09 |
Keywords
- Animal Breeding
- Applied Statistics
- Quantitative Genetics (incl Disease and Trait Mapping Genetics)
Fingerprint
Dive into the research topics of 'Cheverud revisited: Scope for joint modelling of genetic and environmental covariance matrices'. Together they form a unique fingerprint.Cite this
- APA
- Author
- BIBTEX
- Harvard
- Standard
- RIS
- Vancouver