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  • 标题:Random Clustering Based on the Conditional Inverse Gaussian-Poisson Distribution
  • 本地全文:下载
  • 作者:Nobuaki Hoshino
  • 期刊名称:JOURNAL OF THE JAPAN STATISTICAL SOCIETY
  • 印刷版ISSN:1882-2754
  • 电子版ISSN:1348-6365
  • 出版年度:2003
  • 卷号:33
  • 期号:1
  • 页码:105-117
  • DOI:10.14490/jjss.33.105
  • 出版社:JAPAN STATISTICAL SOCIETY
  • 摘要:The present article describes a Conditional Inverse Gaussian-Poisson (CIGP) distribution, obtained by conditioning an inverse Gaussian-Poisson population model on its total frequency. This CIGP distribution is equivalent to random partitioning of positive integers, with the possibility for a number of applications in statistical ecology, linguistics and statistical disclosure control to name a few. After showing the marginal moments of the distribution, parameter estimation is discussed. Fitting the CIGP distribution to some typical data sets demonstrates its applicability.
  • 关键词:disclosure risk;frequencies of frequencies;size index;species abundance;superpopulation
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