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Weighted Rayleigh Distribution

Author

Listed:
  • Adetunji K. Ilori

    (Statistics Programme, National Mathematical Center, Kaduna-Lokoja Expressway, Sheda, Kwali Abuja, Nigeria)

  • Omaku P. Enesi

    (Department of Mathematics and Statistics, Federal Polytechnic, Nassarawa)

  • Kole Emmanuel

    (Department of Mathematics and Statistics, Kaduna Polytechnic, Kaduna)

  • Dayo V. Kayode

    (Department of Statistics, University of Abuja, FCT, Nigeria)

  • Adebisi Michael

    (Nigeria Centre for Disease Control and Prevention)

Abstract

This paper introduces the Weighted Rayleigh (WR) distribution by inducing inverted weight function into the existing Rayleigh distribution. Statistical and mathematical expressions of its properties such as Survival Function, Hazard Function, Moments, Moment Generating Function, Mean Deviation and Renyi entropy were explicitly derived. The model’s parameter was estimated using maximum likelihood method of estimation. Two real life data sets on cancer and waiting time before service were considered to assess the flexibility of the Weighted Rayleigh distribution over existing distributions. The distributions performance were compared using Log-likelihood and Akaike Information Criteria (AIC). The Weighted Rayleigh distribution fits the real life data better than the Rayleigh, Inverse Weibull (IW) and Weighted Inverse Weibull (WIW) distributions.

Suggested Citation

  • Adetunji K. Ilori & Omaku P. Enesi & Kole Emmanuel & Dayo V. Kayode & Adebisi Michael, 2024. "Weighted Rayleigh Distribution," International Journal of Research and Innovation in Applied Science, International Journal of Research and Innovation in Applied Science (IJRIAS), vol. 9(8), pages 323-336, August.
    • Handle: RePEc:bjf:journl:v:9:y:2024:i:8:p:323-336
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