The EAS approach to variable selection for multivariate response data in high-dimensional settings
Author:
Affiliation:
1. Duke University, Durham, NC
2. North Carolina State University, Raleigh, NC
Publisher
Institute of Mathematical Statistics
Subject
Statistics and Probability,Statistics, Probability and Uncertainty
Reference56 articles.
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2. NARISETTY, N. N. and HE, X. (2014). Bayesian variable selection with shrinking and diffusing priors. The Annals of Statistics 42 789–817.
3. BAI, R. and GHOSH, M. (2018). High-dimensional multivariate posterior consistency under global–local shrinkage priors. Journal of Multivariate Analysis 167 157–170.
4. BAI, R. and GHOSH, M. (2018). MBSP: Multivariate Bayesian Model with Shrinkage Priors R package version 1.0.
5. BAI, R., MORAN, G. E., ANTONELLI, J. L., CHEN, Y. and BOLAND, M. R. (2020). Spike-and-slab group lassos for grouped regression and sparse generalized additive models. Journal of the American Statistical Association 1–14.
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