Confidence Intervals with Jointly Type-II Censored Samples from Two Exponential Distributions
Abstract Strong consistency and asymptotic normality of the maximum likelihood estimators are established in the context of jointly type-II censored samples from two exponential populations. Large-sample confidence intervals are derived for the individual scale parameters as well as their ratio, and some applications to series and parallel systems are discussed. For the ratio of the scale parameters, an exact confidence procedure is developed on the basis of the failure counts in the two samples, and its asymptotic efficiency is investigated.