Journal
JOURNAL OF STATISTICAL PLANNING AND INFERENCE
Volume 137, Issue 7, Pages 2127-2142Publisher
ELSEVIER SCIENCE BV
DOI: 10.1016/j.jspi.2006.06.043
Keywords
maximum likelihood estimators; approximate maximum likelihood estimators; asymptotic distribution; type-I censoring; type-II censoring; Gibbs sampling; optimum censoring scheme
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A hybrid censoring is a mixture of Type-I and Type-II censoring schemes. This article presents the 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. The 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. (c) 2006 Elsevier B.V. All rights reserved.
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