Bivariate Birnbaum-Saunders distribution and associated inference

Authors:
Debasis Kundu;N. Balakrishnan;A. Jamalizadeh
Affiliations:
Department of Mathematics and Statistics, Indian Institute of Technology Kanpur, Pin 208016, India;Department of Mathematics and Statistics, McMaster University, Hamilton, Ontario, Canada L8S 4K1;Department of Statistics, Faculty of Mathematics and Computer, Shahid Bahonar University of Kerman, Kerman, 76169-14111, Iran
Venue:
Journal of Multivariate Analysis
Year:
2010

Citing 4
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Abstract

Univariate Birnbaum-Saunders distribution has been used quite effectively to model positively skewed data, especially lifetime data and crack growth data. In this paper, we introduce bivariate Birnbaum-Saunders distribution which is an absolutely continuous distribution whose marginals are univariate Birnbaum-Saunders distributions. Different properties of this bivariate Birnbaum-Saunders distribution are then discussed. This new family has five unknown parameters and it is shown that the maximum likelihood estimators can be obtained by solving two non-linear equations. We also propose simple modified moment estimators for the unknown parameters which are explicit and can therefore be used effectively as an initial guess for the computation of the maximum likelihood estimators. We then present the asymptotic distributions of the maximum likelihood estimators and use them to construct confidence intervals for the parameters. We also discuss likelihood ratio tests for some hypotheses of interest. Monte Carlo simulations are then carried out to examine the performance of the proposed estimators. Finally, a numerical data analysis is performed in order to illustrate all the methods of inference discussed here.