Parametric inference for inverted exponentiated family with jointly adaptive progressive type-II censoring

In this paper, we consider the parametric inference for the family of inverted exponentiated distributions under a joint adaptive progressive Type-II censoring scheme. The problem of estimation is considered for this family with common scale and different shape parameters. We obtain maximum likelihood estimators of unknown model parameters. In sequel asymptotic intervals are also constructed. Further, Bayes estimators are derived under squared error loss function and corresponding credible intervals are obtained as well. To support the findings, we perform simulation studies and analyze a real data set to demonstrate the effectiveness of proposed estimation methods.