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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...
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| Autors principals: | , |
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| Format: | Artigo |
| Idioma: | Inglês |
| Publicat: |
BioMed Central
2007
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| Matèries: | |
| Accés en línia: | https://ncbi.nlm.nih.gov/pmc/articles/PMC2682801/ https://ncbi.nlm.nih.gov/pubmed/17897592 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1186/1297-9686-39-5-481 |
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