Interval estimation for Weibull-distributed life data under Type II progressive censoring with random removals.

This paper explores the problem of interval estimation for parameters of Weibull-distributed data, which are Type II progressively censored with random removals. Seven different confidence interval-estimation procedures are considered. Four of them are based on a parametric bootstrapping approach. Others are based on the asymptotic normality method and the likelihood ratio statistic. We conduct a Monte Carlo simulation to evaluate the performance of these procedures based on their lengths and their coverage probabilities. Furthermore, an example is presented to illustrate the application of these procedures.