Statistical inferences based on an adaptive progressive type-II censoring from exponentiated exponential distribution

Abstract

In this paper, the estimation problem (point and interval) is studied under the exponentiated exponential (EE) distribution based on an adaptive progressive type-II censoring scheme. In point estimation, the maximum likelihood estimates (MLE′s) and Bayes estimates (BE′s), based on squared error (SE) and linear exponential (LINEX) loss functions, are computed. Also, the approximate confidence intervals for the parameters of EE distribution are obtained. A comparison study is made between the BE′s and MLE′s using the estimated risks (ER′s) criterion. Finally, point and interval estimations of all parameters are studied based on a generated adaptive type-II progressive censoring sample from a real data set as illustrative example.