Please use this identifier to cite or link to this item: http://repositorio.unicamp.br/jspui/handle/REPOSIP/355987
Type: Artigo
Title: A log Birnbaum–saunders regression model based on the skew-normal distribution under the centred parameterization
Author: Chaves, Nathalia L.
Azevedo, Caio L. N.
Vilca-Labra, Filidor
Nobre, Juvêncio S.
Abstract: In this paper we introduce a new regression model for positive and skewed data, a log Birnbaum–Saunders model based on the centred skew-normal distribution, also presenting several inference tools for this model. Initially, we developed a new version of the skew-sinh-normal distribution, describing some of its properties. For the proposed regression model, we carry out, through the expectation conditional maximization (ECM) algorithm, parameter estimation, model fit assessment, model comparison and residual analysis. Finally, our model accommodates more suitably the asymmetry of the data, compared with the usual log Birnbaum–Saunders model, which is illustrated through a real data analysis
Subject: Algoritmos
Country: Estados Unidos
Editor: International Press
Rights: Fechado
Identifier DOI: 10.4310/SII.2020.v13.n3.a4
Address: https://www.intlpress.com/site/pub/pages/journals/items/sii/content/vols/0013/0003/a004/
Date Issue: 2020
Appears in Collections:IMECC - Artigos e Outros Documentos

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