February 2021 A bivariate fatigue-life regression model and its application to fracture of metallic tools
Helton Saulo, Jeremias Leão, Víctor Leiva, Roberto Vila, Vera Tomazella
Braz. J. Probab. Stat. 35(1): 119-137 (February 2021). DOI: 10.1214/20-BJPS490


The Birnbaum–Saunders distribution has been widely used to model reliability and fatigue data. In this paper, we propose a regression of generalized linear models type based on a new bivariate Birnbaum–Saunders distribution. This is parameterized in terms of its means and allows data to be described in their original scale. We estimate the model parameters and carry out inference with the maximum likelihood method. A case study with real-world reliability data is conducted for motivating our investigation, illustrating the potential applications of the proposed results. We obtain a predictive model which can be a useful addition to the tool-kit of diverse practitioners, reliability engineers, applied statisticians, and data scientists.


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Helton Saulo. Jeremias Leão. Víctor Leiva. Roberto Vila. Vera Tomazella. "A bivariate fatigue-life regression model and its application to fracture of metallic tools." Braz. J. Probab. Stat. 35 (1) 119 - 137, February 2021. https://doi.org/10.1214/20-BJPS490


Received: 1 July 2019; Accepted: 1 September 2020; Published: February 2021
First available in Project Euclid: 6 January 2021

MathSciNet: MR4195763
Digital Object Identifier: 10.1214/20-BJPS490

Keywords: $\mathtt{R}$ software , bivariate Birnbaum–Saunders distribution , fatigue data , maximum likelihood method , predictive models

Rights: Copyright © 2021 Brazilian Statistical Association


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Vol.35 • No. 1 • February 2021
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