文章基本信息

标题：A Novel Generator of Continuous Probability Distributions for the Asymmetric Left-skewed Bimodal Real-life Data with Properties and Copulas
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作者：Wahid A.M.Shehata ; Haitham Yousof ; Mohamed Aboraya 等
期刊名称：Pakistan Journal of Statistics and Operation Research
印刷版ISSN：2220-5810
出版年度：2021
卷号：17
期号：4
页码：943-961
DOI：10.18187/pjsor.v17i4.3903
语种：English
出版社：College of Statistical and Actuarial Sciences
摘要：This paper presents a novel two-parameter G family of distributions. Relevant statistical properties such as the ordinary moments, incomplete moments and moment generating function are derived. Using common copulas, some new bivariate type G families are derived. Special attention is devoted to the standard exponential base line model. The density of the new exponential extension can be â€œasymmetric and right skewed shapeâ€ with no peak, â€œasymmetric right skewed shapeâ€ with one peak, â€œsymmetric shapeâ€ and â€œasymmetric left skewed shapeâ€ with one peak. The hazard rate of the new exponential distribution can be â€œincreasingâ€, â€œU-shapeâ€, â€œdecreasingâ€ and â€œJ-shapeâ€. The usefulness and flexibility of the new family is illustrated by means of two applications to real data sets. The new family is compared with many common G families in modeling relief times and survival times data sets.
关键词：Poisson Family; Generalized Weibull Family; compounding; Farlie-Gumbel-Morgenstern; Clayton copula; Modeling; Lomax distribution; Ali-Mikhail-Haq copula