Different Approaches to Estimation of the Gompertz Distribution under the Progressive Type-II Censoring Scheme

Abstract EN

This paper provides an estimation method for an unknown parameter by extending weighted least-squared and pivot-based methods to the Gompertz distribution with the shape and scale parameters under the progressive Type-II censoring scheme, which induces a consistent estimator and an unbiased estimator of the scale parameter.

In addition, a way to deal with a nuisance parameter is provided in the pivot-based approach.

For evaluation and comparison, the Monte Carlo simulations are conducted, and real data are analyzed.