Estimating and prediction for alpha-power Pareto distribution based on progressive type-II censoring scheme

Abstract EN

In Statistical theory, inclusion of an additional parameter to standard distributions is a usual practice.

Mahdavi and Kundu (2017) presented a method, called alpha power transformation, for including an extra parameter in continuous distribution.

Basically, the idea was introduced to incorporate skewness to the baseline distribution.

In this paper, the parameters of the alpha-power Pareto distribution, reliability and hazard rate functionsare estimated under progressive censoring Type-II scheme with random removal.

The model parameters are estimated using the maximum likelihood estimation method.

Further, the asymptotic confidence intervals for the model parameters are discussed.

Maximum likelihood prediction (point and bounds) is considered for future order statistics under progressive Type-II censored informative samples.

Numerical study is given and some interesting comparisons are presented to illustrate the theoretical results.

Moreover, the results are applied to real data sets.