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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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Bibliografiske detaljer
Udgivet i:Biometrika
Main Authors: Chakraborty, Antik, Bhattacharya, Anirban, Mallick, Bani K.
Format: Artigo
Sprog:Inglês
Udgivet: 2019
Fag:
Online adgang: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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