Yazar "Afify, Ahmed Z." seçeneğine göre listele

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    The Burr X Pareto distribution: properties, applications and VaR estimation
    (MDPI, 2018) Korkmaz, Mustafa Çağatay; Altun, Emrah; Yousof, Haitham M.; Afify, Ahmed Z.; Nadarajah, Saralees
    In this paper, a new three-parameter Pareto distribution is introduced and studied. We discuss various mathematical and statistical properties of the new model. Some estimation methods of the model parameters are performed. Moreover, the peaks-over-threshold method is used to estimate Value-at-Risk (VaR) by means of the proposed distribution. We compare the distribution with a few other models to show its versatility in modelling data with heavy tails. VaR estimation with the Burr X Pareto distribution is presented using time series data, and the new model could be considered as an alternative VaR model against the generalized Pareto model for financial institutions.
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    The fréchet topp leone-g family of distributions: Properties, characterizations and applications
    (Springer Science and Business Media Deutschland GmbH, 2021) Reyad, Hesham; Korkmaz, Mustafa Çağatay; Afify, Ahmed Z.; Hamedani G.G.; Othman, Soha
    A new family of continuous distributions which ensure model flexiblity, is introduced based on the Fréchet distribution and Topp Leone-G family. Two special sub-models of the new family are discussed. We provide some distributional properties of this family in the general setting such as the series expansions of density, moments, generating function, stress strength model, Rényi and Shannon entropies, probability weighted moments and order statistics. Certain characterizations of the proposed family are presented. The maximum likelihood estimates and the observed information matrix are obtained for the model parameters. We assess the performance of the maximum likelihood estimators by means of a graphical simulation study. The potentiality of the new class is shown via two applications to real data sets.
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    The Weibull Marshall-Olkin family: Regression model and application to censored data
    (Taylor & Francis Inc, 2019) Korkmaz, Mustafa Çağatay; Cordeiro, Gauss M.; Yousof, Haitham M.; Pescim, Rodrigo R.; Afify, Ahmed Z.; Nadarajah, Saralee
    We introduce a new class of distributions called the Weibull Marshall-Olkin-G family. We obtain some of its mathematical properties. The special models of this family provide bathtub-shaped, decreasing-increasing, increasing-decreasing-increasing, decreasing-increasing-decreasing, monotone, unimodal and bimodal hazard functions. The maximum likelihood method is adopted for estimating the model parameters. We assess the performance of the maximum likelihood estimators by means of two simulation studies. We also propose a new family of linear regression models for censored and uncensored data. The flexibility and importance of the proposed models are illustrated by means of three real data sets.
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    The xgamma family: Censored regression modelling and applications
    (National Statistical Institute, 2020) Cordeiro, Gauss M.; Altun, Emrah; Korkmaz, Mustafa Çağatay; Pescim, Rodrigo R.; Afify, Ahmed Z.; Yousof, Haitham M.
    In this paper, a new family of distributions with one extra shape parameter, called the xgamma-G, is proposed. comprehensive treatment of some of its mathematical properties including ordinary and incomplete moments and quantile and generating functions are derived. The unknown model parameters are estimated by the maximum likelihood method and the performance of the maximum likelihood estimators are assessed via two extensive simulation studies. Additionally, the log-location-scale regression model for censored data based on a special member of the family is introduced. The usefulness of the proposed models is illustrated utilizing three real data sets.