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Exact inference for exponential distribution with multiply type-I censored data. (English) Zbl 1385.62030

Summary: We focus on exact inference for exponential distribution under multiple type-I censoring, which is a general form of type-I censoring and represents that the units are terminated at different times. The maximum likelihood estimate of the mean parameter is calculated. Further, the distribution of maximum likelihood estimate is derived and it yields an exact lower confidence limit for the mean parameter. Based on a simulation study, we conclude that the exact limit outperforms the bootstrap limit in terms of the coverage probability and average limit. Finally, a real dataset is analyzed for illustration.

MSC:

62N05 Reliability and life testing
62N01 Censored data models
62F10 Point estimation
62F25 Parametric tolerance and confidence regions
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References:

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