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.
Tse
Siu-Keung
SK
Department of Management Sciences, City University of Hong Kong, Hong Kong. MSSKTSE@cityu.edu.hk
Xiang
Liming
L
D000818:Animals; D001699:Biometry / Q000379:methods*; D003198:Computer Simulation; D016001:Confidence Intervals; D007313:Insecta / Q000187:drug effects; D007306:Insecticides / Q000592:standards; D016013:Likelihood Functions; D015233:Models, Statistical; D009010:Monte Carlo Method; D016011:Normal Distribution; D015588:Observer Variation; D016019:Survival Analysis
D007306:Insecticides