文章基本信息

标题：THE EXPONENTIATED GENERALIZED EXTENDED PARETO DISTRIBUTION
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作者：Thiago A. N. De Andrade ; Luz M. Zea
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：781-800
DOI：10.6339/JDS.201810_16(4).00007
出版社：Tingmao Publish Company
摘要：We define and study a three-parameter model with positive real support called the exponentiated generalized extended Pareto distribution. We provide a comprehensive mathematical treatment and prove that the formulas related to the new model are simple and manageable. We study the behaviour of the maximum likelihood estimates for the model parameters using Monte Carlo simulation. We take advantage of applied studies and offer two applications to real data sets that proves empirically the power of adjustment of the new model when compared to another twelve lifetime distributions..
关键词：Applied studies; Exponentiated generalized model; Extended Pareto distribution; Lehmann’s alternatives; Monte Carlo simulation.