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VARIABLE SELECTION FOR HIGH DIMENSIONAL MULTIVARIATE OUTCOMES
We consider variable selection for high-dimensional multivariate regression using penalized likelihoods when the number of outcomes and the number of covariates might be large. To account for within-subject correlation, we consider variable selection when a working precision matrix is used and when...
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| Publicado no: | Stat Sin |
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| Main Authors: | , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
2014
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC5478010/ https://ncbi.nlm.nih.gov/pubmed/28642637 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.5705/ss.2013.019 |
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