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On hybrid censored Weibull distribution. (English) Zbl 1120.62081
Summary: A hybrid censoring is a mixture of Type-I and Type-II censoring schemes. This article presents statistical inferences on Weibull parameters when the data are hybrid censored. The maximum likelihood estimators (MLEs) and the approximate maximum likelihood estimators are developed for estimating the unknown parameters. Asymptotic distributions of the MLEs are used to construct approximate confidence intervals. Bayes estimates and the corresponding highest posterior density credible intervals of the unknown parameters are obtained under suitable priors on the unknown parameters and using the Gibbs sampling procedure. A method of obtaining the optimum censoring scheme based on the maximum information measure is also developed. Monte Carlo simulations are performed to compare the performances of the different methods and one data set is analyzed for illustrative purposes.

MSC:
62N02 Estimation in survival analysis and censored data
62F15 Bayesian inference
62N01 Censored data models
62E20 Asymptotic distribution theory in statistics
62F25 Parametric tolerance and confidence regions
65C05 Monte Carlo methods
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