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Interval estimation for Weibull-distributed life data under Type II progressive censoring with random removals
1Department of Management Sciences, City University of Hong Kong, Hong Kong. MSSKTSE@cityu.edu.hk
Abstract:
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.
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