A generalized class of skew distributions and associated robust quantile regression models
A generalized class of skew distributions and associated robust quantile regression models
复制标题
一类广义的偏斜分布和相关的稳健分位数回归模型
DOI：
--
复制
发表时间：
2014
期刊：
影响因子：
--
通讯作者：
R. Gerlach
中科院分区：
文献类型：
--
作者：
N. Wichitaksorn;S. Choy;R. Gerlach
本文提出了一个广义的一类单变量偏态分布，通过划分两个正态（高斯）分布的比例混合构造。建议的分布有一个偏度参数定义在区间（0，1），允许直接应用到参数分位数回归。采用尺度混合的法线有利于通过马尔可夫链蒙特卡罗方法进行有效的估计。两个模拟研究，一个偏误回归模型估计，其他参数分位数回归模型显示有利的估计性能。两个相应的实证研究，一个分析美国市场的回报，其他婴儿出生体重数据进一步说明了拟议的分布和估计。加拿大统计杂志42：579-596; 2014 © 2014加拿大统计学会
This article proposes a generalized class of univariate skew distributions that are constructed through partitioning two scaled mixture of normal (Gaussian) distributions. The proposed distributions have a skewness parameter defined in the interval (0,1), allowing direct application to parametric quantile regression. Employing scale mixture of normals facilitates efficient estimation via Markov chain Monte Carlo methods. Two simulation studies, one on estimation with skew error regression models, the other on parametric quantile regression models reveal favourable estimation properties. Two corresponding empirical studies, one analysing U.S. market returns, the other on infant birthweight data further illustrate the proposed distributions and their estimation. The Canadian Journal of Statistics 42: 579–596; 2014 © 2014 Statistical Society of Canada