Decoupling shrinkage and selection in Bayesian linear models: a posterior summary perspective
Methodology
2014-08-05 v1
Abstract
Selecting a subset of variables for linear models remains an active area of research. This paper reviews many of the recent contributions to the Bayesian model selection and shrinkage prior literature. A posterior variable selection summary is proposed, which distills a full posterior distribution over regression coefficients into a sequence of sparse linear predictors.
Cite
@article{arxiv.1408.0464,
title = {Decoupling shrinkage and selection in Bayesian linear models: a posterior summary perspective},
author = {P. Richard Hahn and Carlos M. Carvalho},
journal= {arXiv preprint arXiv:1408.0464},
year = {2014}
}
Comments
30 pages, 6 figures, 2 tables