A generalized class of skew distributions and associated robust quantile regression models
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- Nuttanan Wichitaksorn
- School of Mathematics and Statistics University of Canterbury Christchurch 8140 New Zealand
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- S. T. Boris Choy
- Discipline of Business Analytics University of Sydney New South Wales 2006 Australia
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- Richard Gerlach
- Discipline of Business Analytics University of Sydney New South Wales 2006 Australia
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説明
<jats:title>Abstract</jats:title><jats:sec><jats:label/><jats:p>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.<jats:italic>The Canadian Journal of Statistics</jats:italic>42: 579–596; 2014 © 2014 Statistical Society of Canada</jats:p></jats:sec>
収録刊行物
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- Canadian Journal of Statistics
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Canadian Journal of Statistics 42 (4), 579-596, 2014-10-23
Wiley