May 2021 On a transform for modeling skewness
Li Kang, Paul Damien, Stephen Walker
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Braz. J. Probab. Stat. 35(2): 335-350 (May 2021). DOI: 10.1214/20-BJPS477

Abstract

In many applications, data exhibit skewness and in this paper we present a new family of density functions modeling skewness based on a transformation, analogous to those of location and scale. Here we note that location will always refer to mode. Hence, in order to model data to include shape, we need only to find a family of densities exhibiting a variety of shapes, since we can obtain the other three properties via the transformations. The chosen class of densities with the variety of shape is, we argue, the simplest available. Illustrations including regression and time series models are given.

Acknowledgments

The authors are grateful for the comments and suggestions of a referee and Associate Editor on an earlier version of the paper.

Citation

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Li Kang. Paul Damien. Stephen Walker. "On a transform for modeling skewness." Braz. J. Probab. Stat. 35 (2) 335 - 350, May 2021. https://doi.org/10.1214/20-BJPS477

Information

Received: 1 November 2019; Accepted: 1 May 2020; Published: May 2021
First available in Project Euclid: 24 March 2021

Digital Object Identifier: 10.1214/20-BJPS477

Keywords: auxiliary variable , Bayesian inference , Markov chain Monte Carlo , mixtures of uniforms

Rights: Copyright © 2021 Brazilian Statistical Association

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Vol.35 • No. 2 • May 2021
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