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New Goodness-of-Fit Tests for the Kumaraswamy Distribution

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  • David E. Giles

    (Department of Economics, University of Victoria, 3800 Finnerty Rd, Victoria, BC V8W 2Y2, Canada
    Retired.
    Current address: 58 Rock Lake Court, RR1, Bancroft, ON K0L 1C0, Canada)

Abstract

The two-parameter distribution known as the Kumaraswamy distribution is a very flexible alternative to the beta distribution with the same (0,1) support. Originally proposed in the field of hydrology, it has subsequently received a good deal of positive attention in both the theoretical and applied statistics literatures. Interestingly, the problem of testing formally for the appropriateness of the Kumaraswamy distribution appears to have received little or no attention to date. To fill this gap, in this paper, we apply a “biased transformation” methodology to several standard goodness-of-fit tests based on the empirical distribution function. A simulation study reveals that these (modified) tests perform well in the context of the Kumaraswamy distribution, in terms of both their low size distortion and respectable power. In particular, the “biased transformation” Anderson–Darling test dominates the other tests that are considered.

Suggested Citation

  • David E. Giles, 2024. "New Goodness-of-Fit Tests for the Kumaraswamy Distribution," Stats, MDPI, vol. 7(2), pages 1-16, April.
  • Handle: RePEc:gam:jstats:v:7:y:2024:i:2:p:23-388:d:1380521
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    References listed on IDEAS

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    1. James B. McDonald, 2008. "Some Generalized Functions for the Size Distribution of Income," Economic Studies in Inequality, Social Exclusion, and Well-Being, in: Duangkamon Chotikapanich (ed.), Modeling Income Distributions and Lorenz Curves, chapter 3, pages 37-55, Springer.
    2. Silvia Ferrari & Francisco Cribari-Neto, 2004. "Beta Regression for Modelling Rates and Proportions," Journal of Applied Statistics, Taylor & Francis Journals, vol. 31(7), pages 799-815.
    3. Leandro Medina & Friedrich Schneider, 2019. "Shedding Light on the Shadow Economy: A Global Database and the Interaction with the Official One," CESifo Working Paper Series 7981, CESifo.
    4. Pablo Mitnik & Sunyoung Baek, 2013. "The Kumaraswamy distribution: median-dispersion re-parameterizations for regression modeling and simulation-based estimation," Statistical Papers, Springer, vol. 54(1), pages 177-192, February.
    5. Courard-Hauri, David, 2007. "Using Monte Carlo analysis to investigate the relationship between overconsumption and uncertain access to one's personal utility function," Ecological Economics, Elsevier, vol. 64(1), pages 152-162, October.
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