JSM 2011 Online Program

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Abstract Details

Activity Number: 73
Type: Contributed
Date/Time: Sunday, July 31, 2011 : 4:00 PM to 5:50 PM
Sponsor: Section on Bayesian Statistical Science
Abstract - #302390
Title: Partially Bayesian Variable Selection in Linear Regression
Author(s): Douglas A. Noe*+
Companies: Miami University
Address: Department of Statistics, Oxford, OH, 45056,
Keywords: qualitative prior ; relative importance ; LASSO

We consider the problem of variable selection for linear regression in the case where prior knowledge is qualitative in nature. Rather than specifying priors on coefficient parameters, we incorporate information about the relative importance of each available predictor variable. A modified LASSO procedure then aids in variable selection. We will illustrate the properties of our approach using widely-available data examples.

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