An Asymmetric Bimodal Distribution with Application to Quantile Regression

In this article, we study an extension of the sinh Cauchy model in order to obtain asymmetric bimodality. The behavior of the distribution may be either unimodal or bimodal. We calculate its cumulative distribution function and use it to carry out quantile regression. We calculate the maximum likeli...

Full description

Bibliographic Details
Main Authors: Yolanda M. Gómez, Emilio Gómez-Déniz, Osvaldo Venegas, Diego I. Gallardo, Héctor W. Gómez
Format: Article
Language:English
Published: MDPI AG 2019-07-01
Series:Symmetry
Subjects:
Online Access:https://www.mdpi.com/2073-8994/11/7/899
Description
Summary:In this article, we study an extension of the sinh Cauchy model in order to obtain asymmetric bimodality. The behavior of the distribution may be either unimodal or bimodal. We calculate its cumulative distribution function and use it to carry out quantile regression. We calculate the maximum likelihood estimators and carry out a simulation study. Two applications are analyzed based on real data to illustrate the flexibility of the distribution for modeling unimodal and bimodal data.
ISSN:2073-8994