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Confidence interval estimation of the common mean of several gamma populations

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  • Li Yan

Abstract

Gamma distributions are widely used in applied fields due to its flexibility of accommodating right-skewed data. Although inference methods for a single gamma mean have been well studied, research on the common mean of several gamma populations are sparse. This paper addresses the problem of confidence interval estimation of the common mean of several gamma populations using the concept of generalized inference and the method of variance estimates recovery (MOVER). Simulation studies demonstrate that several proposed approaches can provide confidence intervals with satisfying coverage probabilities even at small sample sizes. The proposed methods are illustrated using two examples.

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  • Li Yan, 2022. "Confidence interval estimation of the common mean of several gamma populations," PLOS ONE, Public Library of Science, vol. 17(6), pages 1-13, June.
    • Handle: RePEc:plo:pone00:0269971
    DOI: 10.1371/journal.pone.0269971
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    References listed on IDEAS

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    1. Samaradasa Weerahandi & Vance W. Berger, 1999. "Exact Inference for Growth Curves with Intraclass Correlation Structure," Biometrics, The International Biometric Society, vol. 55(3), pages 921-924, September.
    2. Kalimuthu Krishnamoorthy & Xiao Wang, 2016. "Fiducial confidence limits and prediction limits for a gamma distribution: Censored and uncensored cases," Environmetrics, John Wiley & Sons, Ltd., vol. 27(8), pages 479-493, December.
    3. Ching-Hui Chang & Jyh-Jiuan Lin & Nabendu Pal, 2011. "Testing the equality of several gamma means: a parametric bootstrap method with applications," Computational Statistics, Springer, vol. 26(1), pages 55-76, March.
    4. Kalimuthu Krishnamoorthy & Meesook Lee & Wang Xiao, 2015. "Likelihood ratio tests for comparing several gamma distributions," Environmetrics, John Wiley & Sons, Ltd., vol. 26(8), pages 571-583, December.
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