Bayesian variable selection in binary quantile regression
- 주제(키워드) Bayes factor , Bayesian model selection , Markov chain Monte Carlo , Quantile regression
- 등재 SCIE, SCOPUS
- 발행기관 Elsevier
- 발행년도 2016
- 총서유형 Journal
- URI http://www.dcollection.net/handler/ewha/000000135481
- 본문언어 영어
- Published As http://dx.doi.org/10.1016/j.spl.2016.07.001
- 저작권 이화여자대학교 논문은 저작권에 의해 보호받습니다.
초록/요약
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. © 2016
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