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Goodness-of-Fit Test for the Kumaraswamy Distribution via Energy Distance Approach with Applications to Real Data

Author

Listed:
  • Joseph Njuki

    (Department of Mathematics and Statistics, Coastal Carolina University, Conway, SC 29526, USA)

  • Thomas Gilbert

    (Department of Mathematics and Statistics, Coastal Carolina University, Conway, SC 29526, USA)

Abstract

In this article, we develop a goodness-of-fit test for the Kumaraswamy distribution based on energy statistics. Due to the availability of its quantile (inverse) function, the Kumaraswamy distribution has been shown to be the preferred alternative to the Beta distribution, since both have bounded support in the ( 0 , 1 ) interval. The proposed test procedure is simple and more powerful against general alternatives. Under different settings, simulations show that the proposed test is capable of being well controlled for any given significance (nominal) levels. In terms of power comparisons, the proposed test outperforms other existing methods in different settings. We then apply the proposed test to two real datasets (electricity access data and underground economy index) to demonstrate its competitiveness and usefulness.

Suggested Citation

  • Joseph Njuki & Thomas Gilbert, 2026. "Goodness-of-Fit Test for the Kumaraswamy Distribution via Energy Distance Approach with Applications to Real Data," Stats, MDPI, vol. 9(3), pages 1-20, May.
    • Handle: RePEc:gam:jstats:v:9:y:2026:i:3:p:50-:d:1948527
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