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.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have