Estimation of Matusita measure between generalized inverted exponential distributions under progressive first-failure censored data

Abstract

Inference for Matusita measure between independent generalized inverted exponential distributions (GIEDs) is investigated under progressive first-failure censoring. When both GIEDs have common scale but different shape parameters, maximum likelihood estimator of the Matusita measure along with the existence and uniqueness of model estimators are established. Approximate confidence interval is constructed in consequence. Alternative generalized point and interval estimates are further constructed based on proposed pivotal quantities. For comparison, bootstrap confidence intervals are also provided. In addition, likelihood and generalized estimates for the Matusita measure are also discussed when two GIEDs have unequal parameters. Further, likelihood ratio testing is provided for comparing the equivalence of the interested parameters. Finally, extensive simulation studies are carried out to evaluate the performances of different methods, and two real life examples are presented for application.