A Regression Model for Positive Data Based on the Slashed Half-Normal Distribution

Yolanda M. Gómez; Diego I. Gallardo; Mário de Castro

doi:10.57805/revstat.v19i4.354

A Regression Model for Positive Data Based on the Slashed Half-Normal Distribution

Authors

Yolanda M. Gómez Universidad de Atacama https://orcid.org/0000-0002-8092-9666
Diego I. Gallardo Universidad de Atacama https://orcid.org/0000-0001-8184-7403
Mário de Castro Universidade de São Paulo https://orcid.org/0000-0001-8685-9470

DOI:

https://doi.org/10.57805/revstat.v19i4.354

Keywords:

EM algorithm, gamma distribution, half-normal distribution, slashed distribution

Abstract

In this paper, we discuss several aspects about the slashed half-normal distribution. We reparameterize the model based on the mean and we perform comparisons with well-known regression models for positive data. Maximum likelihood estimation of the parameters is carried out through the expectation-maximization algorithm. Some properties of the estimators and two kinds of residuals are assessed in a simulation study. Two real datasets illustrated the proposed model as well as other three models for the sake of comparison.

Downloads

REVSTAT2021v19n4_5

Published

2021-12-02

How to Cite

M. Gómez , Y., I. Gallardo , D., & de Castro , M. (2021). A Regression Model for Positive Data Based on the Slashed Half-Normal Distribution. REVSTAT-Statistical Journal, 19(4), 553–573. https://doi.org/10.57805/revstat.v19i4.354