文章基本信息

标题：THE INVERSE WEIBULL GENERATOR OF DISTRIBUTIONS : PROPERTIES AND APPLICATIONS
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作者：Amal S. Hassan ; Said G. Nassr
期刊名称：Journal of Data Science
印刷版ISSN：1680-743X
电子版ISSN：1683-8602
出版年度：2018
卷号：16
期号：4
页码：723-742
DOI：10.6339/JDS.201810_16(4).00004
出版社：Tingmao Publish Company
摘要：In this paper, we introduce a new family of univariate distributions with two extra positive parameters generated from inverse Weibull random variable called the inverse Weibull generated (IW-G) family. The new family provides a lot of new models as well as contains two new families as special cases. We explore four special models for the new family. Some mathematical properties of the new family including quantile function, ordinary and incomplete moments, probability weighted moments, Rѐnyi entropy and order statistics are derived. The estimation of the model parameters is performed via maximum likelihood method. Applications show that the new family of distributions can provide a better fit than several existing lifetime models..
关键词：Inverse Weibull distribution; Moments; quantiles; Inverse Weibull-G family