首页 | 本学科首页   官方微博 | 高级检索  
     


Bayesian analysis of a Tobit quantile regression model
Authors:Keming Yu  Julian Stander
Affiliation:1. Department of Mathematical Sciences, Brunel University, Uxbridge, UB8 3PH, UK;2. School of Mathematics and Statistics, University of Plymouth, UK
Abstract:This paper develops a Bayesian framework for Tobit quantile regression. Our approach is organized around a likelihood function that is based on the asymmetric Laplace distribution, a choice that turns out to be natural in this context. We discuss families of prior distributions on the quantile regression vector that lead to proper posterior distributions with finite moments. We show how the posterior distribution can be sampled and summarized by Markov chain Monte Carlo methods. A method for comparing alternative quantile regression models is also developed and illustrated. The techniques are illustrated with both simulated and real data. In particular, in an empirical comparison, our approach out-performed two other common classical estimators.
Keywords:C14   C24
本文献已被 ScienceDirect 等数据库收录!
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号