Yazar "El-Morshedy, Mahmoud" seçeneğine göre listele

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    The extended gamma distribution with regression model and applications
    (American Institute of Mathematical Sciences, 2021) Altun, Emrah; Korkmaz, Mustafa Çağatay; El-Morshedy, Mahmoud; Eliwa, M. S.
    This paper introduces a new extension of the gamma distribution, named as a new extended gamma distribution, via mixture representation of xgamma and gamma distributions. The statistical properties of the proposed distribution are derived such as moment generating and characteristic functions, variance, skewness, and kurtosis measures, Lorenz curve, and mean residual life function. The maximum likelihood, parametric bootstrap, method of moments, least squares, and weighted least squares estimation methods are considered to obtain the unknown model parameters. The finite sample performance of estimation methods is discussed via a simulation study. Using the proposed distribution, we propose a new regression model for the right-skewed response variable as an alternative to the gamma regression model. Two real data sets are analyzed to convince the readers for the usefulness of the proposed model.
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    The log exponential-power distribution: Properties, estimations and quantile regression model
    (MDPI, 2021) Korkmaz, Mustafa Çağatay; Altun, Emrah; Alizadeh, Morad; El-Morshedy, Mahmoud
    Recently, bounded distributions have attracted attention. These distributions are frequently used in modeling rate and proportion data sets. In this study, a new alternative model is proposed for modeling bounded data sets. Parameter estimations of the proposed distribution are obtained via maximum likelihood method. In addition, a new regression model is defined under the proposed distribution and its residual analysis is examined. As a result of the empirical studies on real data sets, it is observed that the proposed regression model gives better results than the unit-Weibull and Kumaraswamy regression models.
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    A new flexible family of continuous distributions: the additive Odd-G family
    (MDPI AG, 2021) Altun, Emrah; Korkmaz, Mustafa Çağatay; El-Morshedy, Mahmoud; S. Eliwa, Mohamed
    This paper introduces a new family of distributions based on the additive model structure. Three submodels of the proposed family are studied in detail. Two simulation studies were performed to discuss the maximum likelihood estimators of the model parameters. The log location-scale regression model based on a new generalization of the Weibull distribution is introduced. Three datasets were used to show the importance of the proposed family. Based on the empirical results, we concluded that the proposed family is quite competitive compared to other models.