On mean-based bivariate Birnbaum-Saunders distributions: Properties, inference and application

Helton Saulo, Jeremias Leão, Roberto Vila, Victor Leiva, Vera Tomazella

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

Birnbaum-Saunders models have been widely used to describe data following positive-skew distributions. In this article, we introduce a bivariate Birnbaum-Saunders distribution which has the mean as one of its parameters, allowing us to mimic the standard parameterization of the normal distribution, but in an asymmetric framework. We derive some properties of the mean-based bivariate Birnbaum-Saunders distribution useful for statistical and reliability analyses. Maximum likelihood and modified moment estimations of the model parameters and associated inference are considered. A simulation study is conducted to evaluate the performance of the corresponding estimators and coverage probabilities of confidence intervals are also discussed. Finally, a real-world data analysis is carried out for illustrating the potential of the proposed model.

Original languageEnglish
Pages (from-to)6032-6056
Number of pages25
JournalCommunications in Statistics - Theory and Methods
Volume49
Issue number24
DOIs
StatePublished - 2020
Externally publishedYes

Keywords

  • Maximum likelihood and moment estimators
  • Monte Carlo simulations
  • R software
  • multivariate distributions
  • reliability analysis

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