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May 2019 A new log-linear bimodal Birnbaum–Saunders regression model with application to survival data
Francisco Cribari-Neto, Rodney V. Fonseca
Braz. J. Probab. Stat. 33(2): 329-355 (May 2019). DOI: 10.1214/17-BJPS390

Abstract

The log-linear Birnbaum–Saunders model has been widely used in empirical applications. We introduce an extension of this model based on a recently proposed version of the Birnbaum–Saunders distribution which is more flexible than the standard Birnbaum–Saunders law since its density may assume both unimodal and bimodal shapes. We show how to perform point estimation, interval estimation and hypothesis testing inferences on the parameters that index the regression model we propose. We also present a number of diagnostic tools, such as residual analysis, local influence, generalized leverage, generalized Cook’s distance and model misspecification tests. We investigate the usefulness of model selection criteria and the accuracy of prediction intervals for the proposed model. Results of Monte Carlo simulations are presented. Finally, we also present and discuss an empirical application.

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Francisco Cribari-Neto. Rodney V. Fonseca. "A new log-linear bimodal Birnbaum–Saunders regression model with application to survival data." Braz. J. Probab. Stat. 33 (2) 329 - 355, May 2019. https://doi.org/10.1214/17-BJPS390

Information

Received: 1 February 2017; Accepted: 1 December 2017; Published: May 2019
First available in Project Euclid: 4 March 2019

zbMATH: 07057450
MathSciNet: MR3919026
Digital Object Identifier: 10.1214/17-BJPS390

Keywords: Birnbaum–Saunders distribution , diagnostic analysis , misspecification test , model selection criteria , prediction intervals

Rights: Copyright © 2019 Brazilian Statistical Association

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Vol.33 • No. 2 • May 2019
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