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Minimum Volume Confidence Regions for Parameters of Exponential Distributions from Different Samples

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Abstract

Independent samples from different exponential distributions are available in many statistical applications, for example, in queuing or reliability models, where the random variables describe waiting times and lifetimes, respectively. When two samples are observed, inference is then carried out for two location and two scale parameters. In multivariate setups including common location and common scale parameter assumptions, we provide confidence regions for the parameters of interest, which have minimum Lebesgue measure among all those based on the usual pivotal quantities and with the same or higher confidence level; in particular, they improve in terms of area (volume) upon the standard ‘trapezoidal’ confidence regions being constructed by combining independent univariate pivot statistics. The proposed confidence regions do not require any factorization of the overall confidence level, and their calculations need simple Monte Carlo simulations, only. Although focusing on two complete samples, generalizations of the results to more than two and doubly type-II censored samples are possible.

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Authors and Affiliations

  1. Institute of Statistics, RWTH Aachen University, 52056, Aachen, Germany

    Jens Marcel Lennartz, Stefan Bedbur & Udo Kamps

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  1. Jens Marcel Lennartz
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  2. Stefan Bedbur
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  3. Udo Kamps
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Correspondence to Stefan Bedbur.

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Lennartz, J.M., Bedbur, S. & Kamps, U. Minimum Volume Confidence Regions for Parameters of Exponential Distributions from Different Samples. J Stat Theory Pract 14, 27 (2020). https://doi.org/10.1007/s42519-020-00096-6

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  • DOI: https://doi.org/10.1007/s42519-020-00096-6

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