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Confidence intervals for a two-parameter exponential distribution: One- and two-sample problems

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  • K. Krishnamoorthy
  • Yanping Xia

Abstract

The problems of interval estimating the mean, quantiles, and survival probability in a two-parameter exponential distribution are addressed. Distribution function of a pivotal quantity whose percentiles can be used to construct confidence limits for the mean and quantiles is derived. A simple approximate method of finding confidence intervals for the difference between two means and for the difference between two location parameters is also proposed. Monte Carlo evaluation studies indicate that the approximate confidence intervals are accurate even for small samples. The methods are illustrated using two examples.

Suggested Citation

  • K. Krishnamoorthy & Yanping Xia, 2018. "Confidence intervals for a two-parameter exponential distribution: One- and two-sample problems," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 47(4), pages 935-952, February.
    • Handle: RePEc:taf:lstaxx:v:47:y:2018:i:4:p:935-952
    DOI: 10.1080/03610926.2017.1313983
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    Cited by:

    1. Steffen Rebennack, 2022. "Data-driven stochastic optimization for distributional ambiguity with integrated confidence region," Journal of Global Optimization, Springer, vol. 84(2), pages 255-293, October.
    2. Ngan Hoang-Nguyen-Thuy & K. Krishnamoorthy, 2021. "A method for computing tolerance intervals for a location-scale family of distributions," Computational Statistics, Springer, vol. 36(2), pages 1065-1092, June.

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