Estimation in generalized bivariate Birnbaum–Saunders models

Helton Saulo, N. Balakrishnan, Xiaojun Zhu, Jhon F. B. Gonzales and Jeremias Leão
Additional contact information
N. Balakrishnan: McMaster University
Xiaojun Zhu: McMaster University
Jhon F. B. Gonzales: Universidad Nacional de San Agustín
Jeremias Leão: Universidade Federal do Amazonas

Metrika: International Journal for Theoretical and Applied Statistics, 2017, vol. 80, issue 4, No 3, 427-453

Abstract: Abstract In this paper, we propose two moment-type estimation methods for the parameters of the generalized bivariate Birnbaum–Saunders distribution by taking advantage of some properties of the distribution. The proposed moment-type estimators are easy to compute and always exist uniquely. We derive the asymptotic distributions of these estimators and carry out a simulation study to evaluate the performance of all these estimators. The probability coverages of confidence intervals are also discussed. Finally, two examples are used to illustrate the proposed methods.

Keywords: Asymptotic normality; Bivariate generalized Birnbaum–Saunders distribution; Maximum likelihood estimator; Modified moment estimator (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (1)

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DOI: 10.1007/s00184-017-0612-5

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