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Factor analysis models for structuring covariance matrices of additive genetic effects: a Bayesian implementation
Multivariate linear models are increasingly important in quantitative genetics. In high dimensional specifications, factor analysis (FA) may provide an avenue for structuring (co)variance matrices, thus reducing the number of parameters needed for describing (co)dispersion. We describe how FA can be...
| Autores principales: | , |
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| Formato: | Texto |
| Lenguaje: | English |
| Publicado: |
BioMed Central
2007
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| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2682801/ https://www.ncbi.nlm.nih.gov/pubmed/17897592 http://dx.doi.org/10.1186/1297-9686-39-5-481 |