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Power Law Distribution Based On Maximum Entropy Of Random Permutation Set

Author

Listed:
  • ZIHAN YU

    (Institute of Fundamental and Frontier Science, University of Electronic Science and Technology of China, Chengdu 610054, P. R. China)

  • ZHEN LI

    (��China Mobile Information Technology Center, Beijing 100029, P. R. China)

  • YONG DENG

    (Institute of Fundamental and Frontier Science, University of Electronic Science and Technology of China, Chengdu 610054, P. R. China‡School of Medicine, Vanderbilt University, Nashville, TN 37240, USA)

Abstract

Among all probability distributions, power law distribution is an intriguing one, which has been studied by many researchers. However, the derivation of power law distribution is still an inconclusive topic. For deriving a distribution, there are various methods, among which maximum entropy principle is a special one. Entropy of random permutation set (RPS), as an uncertainty measure of RPS, is a newly proposed entropy with special features. Deriving power law distribution with maximum entropy of RPS is a promising method. In this paper, certain constraints are given to constrain the entropy of RPS. Power law distribution is able to be finally derived with maximum entropy principle. Numerical experiments are done to show characters of proposed derivation.

Suggested Citation

  • Zihan Yu & Zhen Li & Yong Deng, 2023. "Power Law Distribution Based On Maximum Entropy Of Random Permutation Set," FRACTALS (fractals), World Scientific Publishing Co. Pte. Ltd., vol. 31(07), pages 1-11.
    • Handle: RePEc:wsi:fracta:v:31:y:2023:i:07:n:s0218348x23500780
    DOI: 10.1142/S0218348X23500780
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    Cited by:

    1. Zhao, Tong & Li, Zhen & Deng, Yong, 2023. "Information fractal dimension of Random Permutation Set," Chaos, Solitons & Fractals, Elsevier, vol. 174(C).

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