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A Generalized-Alpha–Beta-Skew Normal Distribution with Applications

Author

Listed:
  • Sricharan Shah

    (Dibrugarh University)

  • Partha Jyoti Hazarika

    (Dibrugarh University)

  • Subrata Chakraborty

    (Dibrugarh University)

  • M. Masoom Ali

    (Ball State University)

Abstract

Recently there is a lot of research related to skewed distributions and their growing relevance in data analytics. In the present work we introduce a new generalized version of alpha beta skew normal distribution and some of its basic properties are investigated. Some extensions of the proposed distribution have also been studied. A simulation study has been conducted to see the performance of the obtained estimators of the parameters using Metropolis–Hastings (MH) algorithm. The appropriateness of the proposed distribution has been tested by comparing it with twelve closely related and nested distributions using Akaike Information Criterion. The Likelihood Ratio test has been employed for testing the relevance of the induction of the additional parameters in the proposed model.

Suggested Citation

  • Sricharan Shah & Partha Jyoti Hazarika & Subrata Chakraborty & M. Masoom Ali, 2023. "A Generalized-Alpha–Beta-Skew Normal Distribution with Applications," Annals of Data Science, Springer, vol. 10(4), pages 1127-1155, August.
    • Handle: RePEc:spr:aodasc:v:10:y:2023:i:4:d:10.1007_s40745-021-00325-0
    DOI: 10.1007/s40745-021-00325-0
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    References listed on IDEAS

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    1. Maryam Sharafi & Zahra Sajjadnia & Javad Behboodian, 2017. "A new generalization of alpha-skew-normal distribution," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 46(12), pages 6098-6111, June.
    2. Panayiotis Theodossiou, 1998. "Financial Data and the Skewed Generalized T Distribution," Management Science, INFORMS, vol. 44(12-Part-1), pages 1650-1661, December.
    3. Juárez, Miguel A. & Steel, Mark F. J., 2010. "Model-Based Clustering of Non-Gaussian Panel Data Based on Skew-t Distributions," Journal of Business & Economic Statistics, American Statistical Association, vol. 28(1), pages 52-66.
    4. V. Nekoukhou & M. Alamatsaz, 2012. "A family of skew-symmetric-Laplace distributions," Statistical Papers, Springer, vol. 53(3), pages 685-696, August.
    5. James M. Tien, 2017. "Internet of Things, Real-Time Decision Making, and Artificial Intelligence," Annals of Data Science, Springer, vol. 4(2), pages 149-178, June.
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