Confidence regions for the parameters of an inverted exponentiated Pareto distribution based on progressively Type-II censored samples

In this article, based on progressively type-II censored order statistics, we create balanced confidence regions (BCR) and optimal confidence regions (OCR) for the parameters of an inverted exponentiated Pareto (IEP) distribution. Constraint optimization problem and nonlinear programmings methods are used in order to construct OCRs. Monte Carlo simulation studies are used to evaluate the performance of the methods proposed in this paper. Finally, a numerical example is presented to illustrate the proposed regions.