Adaptive progressive Type-II censoring

Extending the model of progressive Type-II censoring, we introduce an adaption process. It allows us to choose the next censoring number taking into account both the previous censoring numbers and previous failure times. After deriving some distributional results, we show that maximum likelihood estimators coincide with those in deterministic progressive Type-II censoring. Finally, we establish inferential results for the one- and two-parameter exponential distribution. Using the independence of normalized spacings, we present the distributions of the maximum likelihood estimators. Moreover, explicit confidence bounds and tests of hypotheses can be established.