RSS South West: A Loss-Based Prior for Variable Selection in Linear Regression Methods

 
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Wednesday 16 October 2019, 03:00pm

 
Location Room 116, Rolle Building, University of Plymouth, Plymouth, PL4 8AA

Speaker: Cristiano Villa, University of Kent

In this work we propose a novel model prior for variable selection in linear regression. The idea is to determine the prior mass by considering the worth of each of the regression models, given the number of possible covariates under consideration. The worth of a model consists of the information loss and the loss due to model complexity. While the information loss is determined objectively, the loss expression due to model complexity is flexible and, the penalty on model size can be even customized to include some prior knowledge. Some versions of the loss-based prior are proposed and compared empirically. Through simulation studies and real data analyses, we compare the proposed prior to the Scott and Berger prior, for noninformative scenarios, and with the Beta-Binomial prior, for informative scenarios.

Organiser Name Yinghui Wei

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Organising Group(s) RSS South West Local Group

 

 

 

 

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