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Tsallis–Mittag-Leffler distribution and its applications in gas prices

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  • Agahi, Hamzeh
  • Alipour, Mohsen

Abstract

The theory of Mittag-Leffler process is a fundamental concept in probability and stochastic process. This paper introduces the class of Tsallis–Mittag-Leffler distributions. In special case, our results include a new Tsallis q-Weibull distribution, one-parametric Mittag-Leffler distribution and some other well-known distributions. Finally, to illustrate the applicability of our distribution, a real data set on gas prices in time series data based on 100 days moving average is analyzed.

Suggested Citation

  • Agahi, Hamzeh & Alipour, Mohsen, 2020. "Tsallis–Mittag-Leffler distribution and its applications in gas prices," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 541(C).
    • Handle: RePEc:eee:phsmap:v:541:y:2020:i:c:s0378437119320497
    DOI: 10.1016/j.physa.2019.123675
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    References listed on IDEAS

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    1. Zhang, Fode & Ng, Hon Keung Tony & Shi, Yimin, 2018. "On alternative q-Weibull and q-extreme value distributions: Properties and applications," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 490(C), pages 1171-1190.
    2. Sulaiman, Tukur Abdulkadir & Yavuz, Mehmet & Bulut, Hasan & Baskonus, Haci Mehmet, 2019. "Investigation of the fractional coupled viscous Burgers’ equation involving Mittag-Leffler kernel," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 527(C).
    3. Zhang, Fode & Ng, Hon Keung Tony & Shi, Yimin, 2018. "Information geometry on the curved q-exponential family with application to survival data analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 512(C), pages 788-802.
    4. R. Pillai, 1990. "On Mittag-Leffler functions and related distributions," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 42(1), pages 157-161, March.
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    Cited by:

    1. dos Santos, M.A.F. & Menon, L. & Cius, D., 2022. "Superstatistical approach of the anomalous exponent for scaled Brownian motion," Chaos, Solitons & Fractals, Elsevier, vol. 164(C).

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