Multivariate log-Birnbaum–Saunders regression models

Guillermo Martínez-Flórez, Rafael Bráz Azevedo Farias and Germán Moreno-Arenas

Communications in Statistics - Theory and Methods, 2017, vol. 46, issue 20, 10166-10178

Abstract: In this paper, we present a multivariate version of the skewed log-Birnbaum–Saunders regression model. This new family of distributions holds good properties such as marginal variables following univariate skewed log-Birnbaum–Saunders distributions, besides presenting the usual log-Birnbaum–Saunders distribution as a particular case. Furthermore, the model parameters are estimated through maximum-likelihood methods, a closed-form expression for the Fisher’s information matrix is presented, and testing hypothesis for model parameters is performed. Two real datasets are analyzed and results are discussed.

Date: 2017
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DOI: 10.1080/03610926.2016.1231818

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