most citedGibbs posterior for variable selection in high-dimensional classification and data mining

104 citations · 104 across the 2 of their papers we have counts for

collaborators
Showing stat.MEShow all

2 papers · 1 filter

stat.ME2008★ 104 cited

Gibbs posterior for variable selection in high-dimensional classification and data mining

Wenxin Jiang, Martin A. Tanner

In the popular approach of "Bayesian variable selection" (BVS), one uses prior and posterior distributions to select a subset of candidate variables to enter the model. A completel…

stat.ME2007

Locally Adaptive Nonparametric Binary Regression

Sally Wood, Robert Kohn, Remy Cottet +2

A nonparametric and locally adaptive Bayesian estimator is proposed for estimating a binary regression. Flexibility is obtained by modeling the binary regression as a mixture of pr…