Statistical inference for the Gompertz distribution based on Type-II progressively hybrid censored data

ABSTRACT

In this article, the statistical inference for the Gompertz distribution based on Type-II progressively hybrid censored data is discussed. The estimation of the parameters for Gompertz distribution is obtained using maximum likelihood method (MLE) and Bayesian method under three different loss functions. We also proved the existence and uniqueness of the MLE. The one-sample Bayesian prediction intervals are obtained. The work is done for different values of the parameters. We apply the Monto Carlo simulation to compare the proposed methods, also an example is discussed to construct the Prediction intervals.

KEYWORDS:

• Bayesian method
• Gompertz distribution
• Loss functions
• Maximum likelihood estimator (MLE)
• One-sample Bayesian prediction intervals
• Progressive Type-II hybrid censored samples
• Statistical inference

MATHEMATICS SUBJECT CLASSIFICATION:

• 62N05
• 62F15

Acknowledgments

The authors are sincerely grateful to the referees and to the Editor-in-Chief for their many constructive comments and careful reading of the paper.