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- W2525826441 abstract "In this paper, 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 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." @default.
- W2525826441 created "2016-10-07" @default.
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- W2525826441 date "2017-04-21" @default.
- W2525826441 modified "2023-09-24" @default.
- W2525826441 title "Exact inference for exponential distribution with multiply Type-I censored data" @default.
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- W2525826441 doi "https://doi.org/10.1080/03610918.2016.1235187" @default.
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