Birnbaum-Saunders nonlinear regression models
Contribuinte(s) |
UNIVERSIDADE DE SÃO PAULO |
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Data(s) |
20/10/2012
20/10/2012
2009
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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 |
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 |