文章基本信息

标题：THE TRANSMUTED GENERALIZED ODD GENERALIZED EXPONENTIAL -G FAMILY OF DISTRIBUTIONS : THEORY AND APPLICATIONS
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作者：Hesham Reyad ; Soha Othman ; Muhammad Ahsan ul Haq 等
期刊名称：Journal of Data Science
印刷版ISSN：1680-743X
电子版ISSN：1683-8602
出版年度：2019
卷号：17
期号：2
页码：279-298
DOI：10.6339/JDS.201904_17(2).0003
出版社：Tingmao Publish Company
摘要：We propose a new generator of continuous distributions, so called the transmuted generalized odd generalized exponential-G family, which extends the generalized odd generalized exponential-G family introduced by Alizadeh et al. (2017). Some statistical properties of the new family such as; raw and incomplete moments, moment generating function, Lorenz and Bonferroni curves, probability weighted moments, Rényi entropy, stress strength model and order statistics are investigated. The parameters of the new family are estimated by using the method of maximum likelihood. Two real applications are presented to demonstrate the effectiveness of the suggested family.
关键词：Odd Generalized Exponential-G family;Maximum Likelihood;Order Statistic;Stress Strength Model;Transmuted-G family.