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  • 标题:Location Based Generalized Akash Distribution: Properties and Applications
  • 本地全文:下载
  • 作者:Ramajeyam Tharshan ; Pushpakanthie Wijekoon
  • 期刊名称:Open Journal of Statistics
  • 印刷版ISSN:2161-718X
  • 电子版ISSN:2161-7198
  • 出版年度:2020
  • 卷号:10
  • 期号:2
  • 页码:163-187
  • DOI:10.4236/ojs.2020.102013
  • 出版社:Scientific Research Publishing
  • 摘要:In recent years, several statistical finite mixture models have been proposed to model the lifetime data with heterogeneity. The Lindley distribution has been highlighted by many authors for these types of lifetime data analysis. This paper introduces a new Lindley family distribution called location-based generalized Akash distribution (NGAD) with monotonic increasing and bathtub failure rates. The density function of NGAD is flexible to cover the left-skewed, right-skewed and symmetrical shapes with different tail-weights. Its fundamental structural properties and its ability to provide a suitable statistical model for various types of data sets are studied. The maximum likelihood (ML) method is used to estimate its unknown parameters and the performance of ML estimates are examined by a simulation study. Finally, several real-data sets with different characteristics are used to illustrate its flexibility. It is observed that NGAD provides a better fit than some other existing modified Lindley distributions.
  • 关键词:Lindley Distribution;Akash Distribution;Mixture
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