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A Goodness-of-Fit Test for Rayleigh Distribution Based on Hellinger Distance

Author

Listed:
  • S. M. A. Jahanshahi

    (Ferdowsi University of Mashhad)

  • A. Habibi Rad

    (Ferdowsi University of Mashhad)

  • V. Fakoor

    (Ferdowsi University of Mashhad)

Abstract

In this paper, we introduce a new goodness-of-fit test for Rayleigh distribution based on Hellinger distance. In addition, some properties about the proposed test is presented. Then, new proposed test is compared with other goodness-of-fit tests for Rayleigh distribution in the literature in terms of power. Finally, we conclude that the entropy based tests demonstrate a good performance in terms of power and we can choose the Hellinger test as more powerful than the other competitor tests.

Suggested Citation

  • S. M. A. Jahanshahi & A. Habibi Rad & V. Fakoor, 2016. "A Goodness-of-Fit Test for Rayleigh Distribution Based on Hellinger Distance," Annals of Data Science, Springer, vol. 3(4), pages 401-411, December.
    • Handle: RePEc:spr:aodasc:v:3:y:2016:i:4:d:10.1007_s40745-016-0088-6
    DOI: 10.1007/s40745-016-0088-6
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    References listed on IDEAS

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    1. Simos Meintanis & George Iliopoulos, 2003. "Tests of fit for the Rayleigh distribution based on the empirical Laplace transform," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 55(1), pages 137-151, March.
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    Cited by:

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