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  • 标题:The Generalized Additive Weibull-G Family of Distributions
  • 本地全文:下载
  • 作者:Amal S. Hassan ; Saeed E. Hemeda ; Sudhansu S. Maiti
  • 期刊名称:International Journal of Statistics and Probability
  • 印刷版ISSN:1927-7032
  • 电子版ISSN:1927-7040
  • 出版年度:2017
  • 卷号:6
  • 期号:5
  • 页码:65
  • DOI:10.5539/ijsp.v6n5p65
  • 出版社:Canadian Center of Science and Education
  • 摘要:In this paper, we present a new family, depending on additive Weibull random variable as a generator, called the generalized additive Weibull generated-family (GAW-G) of distributions with two extra parameters. The proposed family involves several of the most famous classical distributions as well as the new generalized Weibull-G family which already accomplished by Cordeiro et al. (2015). Four special models are displayed. The expressions for the incomplete and ordinary moments, quantile, order statistics, mean deviations, Lorenz and Benferroni curves are derived. Maximum likelihood method of estimation is employed to obtain the parameter estimates of the family. The simulation study of the new models is conducted. The efficiency and importance of the new generated family is examined through real data sets.
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