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Stats 2018, 1(1), 32-47; https://doi.org/10.3390/stats1010004

A New Extended Birnbaum–Saunders Model: Properties, Regression and Applications

1
Departamento de Estatística, Universidade Federal de Pernambuco, Recife 50740-540, Brazil
2
Departamento de Ciências Exatas, Universidade de São Paulo, São Paulo 13418-900, Brazil
3
Departamento de Matemática Aplicada e Estatística, Universidade de São Paulo, São Paulo 13566-590, Brazil
*
Author to whom correspondence should be addressed.
Received: 19 March 2018 / Revised: 24 April 2018 / Accepted: 14 May 2018 / Published: 18 May 2018
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Abstract

We propose an extended fatigue lifetime model called the odd log-logistic Birnbaum–Saunders–Poisson distribution, which includes as special cases the Birnbaum–Saunders and odd log-logistic Birnbaum–Saunders distributions. We obtain some structural properties of the new distribution. We define a new extended regression model based on the logarithm of the odd log-logistic Birnbaum–Saunders–Poisson random variable. For censored data, we estimate the parameters of the regression model using maximum likelihood. We investigate the accuracy of the maximum likelihood estimates using Monte Carlo simulations. The importance of the proposed models, when compared to existing models, is illustrated by means of two real data sets. View Full-Text
Keywords: Birnbaum–Saunders distribution; fatigue life distribution; lifetime data; maximum likelihood estimation; regression model Birnbaum–Saunders distribution; fatigue life distribution; lifetime data; maximum likelihood estimation; regression model
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).
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MDPI and ACS Style

Cordeiro, G.M.; de Lima, M.C.S.; Ortega, E.M.M.; Suzuki, A.K. A New Extended Birnbaum–Saunders Model: Properties, Regression and Applications. Stats 2018, 1, 32-47.

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