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Bayesian sparse multiple regression for simultaneous rank reduction and variable selection
We develop a Bayesian methodology aimed at simultaneously estimating low-rank and row-sparse matrices in a high-dimensional multiple-response linear regression model. We consider a carefully devised shrinkage prior on the matrix of regression coefficients which obviates the need to specify a prior o...
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| Publié dans: | Biometrika |
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| Auteurs principaux: | , , |
| Format: | Artigo |
| Langue: | Inglês |
| Publié: |
2019
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| Sujets: | |
| Accès en ligne: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7584295/ https://ncbi.nlm.nih.gov/pubmed/33100350 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1093/biomet/asz056 |
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