文献类型：期刊文献

英文题名：Bayesian expectile regression with asymmetric normal distribution

作者：Xing, Ji-Ji[1];Qian, Xi-Yuan[1,2]

机构：[1]East China Univ Sci & Technol, Sch Sci, 130 Meilong Rd,POB 386, Shanghai 200237, Peoples R China;[2]East China Univ Sci & Technol, Res Ctr Econophys, Shanghai, Peoples R China

年份：2017

卷号：46

期号：9

起止页码：4545

外文期刊名：COMMUNICATIONS IN STATISTICS-THEORY AND METHODS

收录：;EI(收录号：20170403282311);WOS:【SSCI(收录号:WOS:000394539100028)，SCI-EXPANDED(收录号:WOS:000394539100028)】；

基金：This work was partially supported by The Software and Integrated Circuit Industry Development Special Funds of Shanghai Economic and Information Commission under Grant No. 140304 and the National High-Tech R\&D Program of China (863 Program) under Grant No. 2015AA020107. We are extremely grateful to Professor Thomas Kneib and the anonymous referee for the extensive comments on the original manuscript.

语种：英文

外文关键词：Asymmetric normal distribution; Bayesian inference; expectile regression; Markov chain Monte Carlo methods; 62F15

摘要：In this paper, we adopt the Bayesian approach to expectile regression employing a likelihood function that is based on an asymmetric normal distribution. We demonstrate that improper uniform priors for the unknown model parameters yield a proper joint posterior. Three simulated data sets were generated to evaluate the proposed method which show that Bayesian expectile regression performs well and has different characteristics comparing with Bayesian quantile regression. We also apply this approach into two real data analysis.