A REGRESSION MODEL FOR POSITIVE DATA BASED ON THE SLASHED HALF-NORMAL DISTRIBUTION

* In this paper, we discuss several aspects about the slashed half-normal distribution. We reparameter-ize 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 expectatio...

Full description

Saved in:
Bibliographic Details
Published inRevstat Vol. 19; no. 4; p. 553
Main Authors Gomez, Yolanda M, Gallardo, Diego I, De Castro, Mario
Format Journal Article
LanguageEnglish
Published Instituto Nacional de Estatistica 01.10.2021
Instituto Nacional de Estatística | Statistics Portugal
Subjects
Algorithms
Analysis
EM algorithm
gamma distribution
half-normal distribution
Quality control
slashed distribution
Chile
Online AccessGet full text

Cover

More Information
Summary:* In this paper, we discuss several aspects about the slashed half-normal distribution. We reparameter-ize 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. Keywords: * EM algorithm; gamma distribution; half-normal distribution; slashed distribution. AMS Subject Classification: * 62F86, 60E05.
ISSN:1645-6726
2183-0371
DOI:10.57805/revstat.v19i4.354