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Mittag-Leffler-Gaussian distribution: Theory and application to real data

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  • Agahi, Hamzeh
  • Alipour, Mohsen

Abstract

In this paper, we introduce the class of Mittag-Leffler-Gaussian distribution which is more flexible than the Gaussian distribution. Some properties of this class are investigated. Then, for two real data sets, the model is examined using the Akaike, Bayesian and small sample Akaike information criteria.

Suggested Citation

  • Agahi, Hamzeh & Alipour, Mohsen, 2019. "Mittag-Leffler-Gaussian distribution: Theory and application to real data," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 156(C), pages 227-235.
    • Handle: RePEc:eee:matcom:v:156:y:2019:i:c:p:227-235
    DOI: 10.1016/j.matcom.2018.07.014
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    References listed on IDEAS

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    1. 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. Haubold, Hans J. & Kabeer, Ashik A. & Kumar, Dilip, 2023. "Analytic forms of thermonuclear functions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 630(C).
    2. Alexander Apelblat, 2020. "Differentiation of the Mittag-Leffler Functions with Respect to Parameters in the Laplace Transform Approach," Mathematics, MDPI, vol. 8(5), pages 1-22, April.

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