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  • 标题:THE EXTENDED ALPHA POWER TRANSFORMED FAMILY OF DISTRIBUTIONS : PROPERTIES AND APPLICATIONS
  • 本地全文:下载
  • 作者:Zubair Ahmad ; Muhammad Ilyas ; G. G. Hamedani
  • 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:4
  • 页码:726-741
  • DOI:10.6339/JDS.201910_17(4).0006
  • 出版社:Tingmao Publish Company
  • 摘要:In this article, a new family of lifetime distributions by adding an additional parameter to the existing distributions is introduced. The new family is called, the extended alpha power transformed family of distributions. For the proposed family, explicit expressions for some mathematical properties along with estimation of parameters through Maximum likelihood Method are discussed. A special sub-model, called the extended alpha power transformed Weibull distribution is considered in detail. The proposed model is very flexible and can be used to model data with increasing, decreasing or bathtub shaped hazard rates. To access the behavior of the model parameters, a small simulation study has also been carried out. For the new family, some useful characterizations are also presented. Finally, the potentiality of the proposed method is showen via analyzing two real data sets taken from reliability engineering and bio-medical fields.
  • 关键词:Family of distributions; Alpha power transformation; Weibull distribution; Moments; Order statistic; Residual life function; Maximum likelihood estimation.
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