Abstract
In this paper, we discuss a regression model based on the bivariate Birnbaum–Saunders distribution. We derive the maximum likelihood estimates of the model parameters and then develop associated inference. Next, we briefly describe likelihood-ratio tests for some hypotheses of interest as well as some interval estimation methods. Monte Carlo simulations are then carried out to examine the performance of the estimators as well as the interval estimation methods. Finally, a numerical data analysis is performed for illustrating all the inferential methods developed here.
Original language | English |
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Pages (from-to) | 853-872 |
Number of pages | 20 |
Journal | Metrika |
Volume | 78 |
Issue number | 7 |
DOIs | |
Publication status | Published - 17 Oct 2015 |
Externally published | Yes |
Keywords
- Akaike information criterion
- Asymptotic confidence interval
- Bivariate Birnbaum–Saunders distribution
- Bootstrap confidence interval
- Least-squares estimators
- Likelihood ratio test
- Maximum likelihood estimates