Bayesian variable selection in binary quantile regression

Man-Suk Oh, Eun Sug Park and Beong-Soo So

Statistics & Probability Letters, 2016, vol. 118, issue C, 177-181

Abstract: We propose a simple Bayesian variable selection method in binary quantile regression. Our method computes the Bayes factors of all candidate models simultaneously based on a single set of MCMC samples from a model that encompasses all candidate models. The method deals with multicollinearity problems and variable selection under constraints.

Keywords: Bayesian model selection; Bayes factor; Quantile regression; Markov chain Monte Carlo (search for similar items in EconPapers)
Date: 2016
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Persistent link: https://EconPapers.repec.org/RePEc:eee:stapro:v:118:y:2016:i:c:p:177-181

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DOI: 10.1016/j.spl.2016.07.001

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