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  • Open Access


    The Arcsine-X Family of Distributions with Applications to Financial Sciences

    Yen Liang Tung1, Zubair Ahmad2, Eisa Mahmoudi2,*

    Computer Systems Science and Engineering, Vol.39, No.3, pp. 351-363, 2021, DOI:10.32604/csse.2021.014270

    Abstract The heavy-tailed distributions are very useful and play a major role in actuary and financial management problems. Actuaries are often searching for such distributions to provide the best fit to financial and economic data sets. In the current study, a prominent method to generate new distributions useful for modeling heavy-tailed data is considered. The proposed family is introduced using trigonometric function and can be named as the Arcsine-X family of distributions. For the purposes of the demonstration, a specific sub-model of the proposed family, called the Arcsine-Weibull distribution is considered. The maximum likelihood estimation method is… More >

  • Open Access


    On Modeling the Medical Care Insurance Data via a New Statistical Model

    Yen Liang Tung1, Zubair Ahmad2,*, G. G. Hamedani3

    CMC-Computers, Materials & Continua, Vol.66, No.1, pp. 113-126, 2021, DOI:10.32604/cmc.2020.012780

    Abstract Proposing new statistical distributions which are more flexible than the existing distributions have become a recent trend in the practice of distribution theory. Actuaries often search for new and appropriate statistical models to address data related to financial and risk management problems. In the present study, an extension of the Lomax distribution is proposed via using the approach of the weighted T-X family of distributions. The mathematical properties along with the characterization of the new model via truncated moments are derived. The model parameters are estimated via a prominent approach called the maximum likelihood estimation… More >

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