Bivariate Birnbaum-Saunders distribution and associated inference

JOURNAL OF MULTIVARIATE ANALYSIS

卷:101

Article

Kundu, Debasis¹  Balakrishnan, N.²  Jamalizadeh, A.³ 

[1] Indian Inst Technol, Dept Math & Stat, Kanpur 208016, Uttar Pradesh, India

[2] McMaster Univ, Dept Math & Stat, Hamilton, ON L8S 4K1, Canada

[3] Shahid Bahonar Univ Kerman, Dept Stat, Fac Math & Comp, Kerman 7616914111, Iran

关键词: Birnbaum-Saunders distribution;    Maximum likelihood estimators;    Modified moment estimators;    Fisher information matrix;    Asymptotic distribution;    Likelihood ratio test;   

DOI  :  10.1016/j.jmva.2009.05.005

来源: Elsevier

【 摘 要 】

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 all 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 call therefore be used effectively as all 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. (C) 2009 Elsevier Inc. All rights reserved.

【 授权许可】

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