Derive power law distribution with maximum Deng entropy. (December 2022)

• Record Type: Journal Article
• Authors: Yu, Zihan; Deng, Yong
• Is Part Of: Chaos, solitons and fractals. Volume 165:Part 2(2022)
• Publication Date: 2022-12
• Subjects: Power law distribution -- Maximum entropy -- Deng entropy -- Mass function -- Probability distribution; Chaotic behavior in systems -- Periodicals; Solitons -- Periodicals; Fractals -- Periodicals; Chaotic behavior in systems; Fractals; Solitons; Periodicals; 003.7
• DOI: 10.1016/j.chaos.2022.112877
• Languages: English
• ISSNs: 0960-0779

Abstract

Abstract: As one of the typical distributions, power law distribution is widely found in natural world. However, how to derive power law is still an open issue. The main contribution of this paper is to propose a method to derive power law distribution with maximum Deng entropy. In the proposed method, Lagrange multiplier approach, combined with the constraint of two given conditions, is used to obtain power law distribution based on maximum Deng entropy. Some numerical examples are used to illustrate the properties of the distribution. Highlights: Power law distribution is derived from mass function. Derivation is based on the maximum entropy principle and Lagrange multiplier approach. Numerical experiments are conducted to test the derivation result.