Birnbaum-Saunders nonlinear regression models


Autoria(s): LEMONTE, Artur J.; CORDEIRO, Gauss M.
Contribuinte(s)

UNIVERSIDADE DE SÃO PAULO

Data(s)

20/10/2012

20/10/2012

2009

Resumo

We introduce, for the first time, a new class of Birnbaum-Saunders nonlinear regression models potentially useful in lifetime data analysis. The class generalizes the regression model described by Rieck and Nedelman [Rieck, J.R., Nedelman, J.R., 1991. A log-linear model for the Birnbaum-Saunders distribution. Technometrics 33, 51-60]. We discuss maximum-likelihood estimation for the parameters of the model, and derive closed-form expressions for the second-order biases of these estimates. Our formulae are easily computed as ordinary linear regressions and are then used to define bias corrected maximum-likelihood estimates. Some simulation results show that the bias correction scheme yields nearly unbiased estimates without increasing the mean squared errors. Two empirical applications are analysed and discussed. Crown Copyright (C) 2009 Published by Elsevier B.V. All rights reserved.

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

FAPESP

CNPq (Brazil)

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Identificador

COMPUTATIONAL STATISTICS & DATA ANALYSIS, v.53, n.12, p.4441-4452, 2009

0167-9473

http://producao.usp.br/handle/BDPI/30784

10.1016/j.csda.2009.06.015

http://dx.doi.org/10.1016/j.csda.2009.06.015

Idioma(s)

eng

Publicador

ELSEVIER SCIENCE BV

Relação

Computational Statistics & Data Analysis

Direitos

restrictedAccess

Copyright ELSEVIER SCIENCE BV

Palavras-Chave #MAXIMUM-LIKELIHOOD-ESTIMATION #INFLUENCE DIAGNOSTICS #BIAS CORRECTION #ESTIMATORS #FAMILY #Computer Science, Interdisciplinary Applications #Statistics & Probability
Tipo

article

original article

publishedVersion