Bayesian variable selection in binary quantile regression Academic Article uri icon

abstract

  • © 2016 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.

published proceedings

  • Statistics & Probability Letters

author list (cited authors)

  • Oh, M., Park, E. S., & So, B

citation count

  • 6

complete list of authors

  • Oh, Man-Suk||Park, Eun Sug||So, Beong-Soo

publication date

  • November 2016