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  • 标题:INFORMATION MEASURES OF RANKED SET SAMPLES IN FARLIE - GUMBEL - MORGENSTERN FAMILY
  • 本地全文:下载
  • 作者:S. Tahmasebi ; A. A. Jafari
  • 期刊名称:Journal of Data Science
  • 印刷版ISSN:1680-743X
  • 电子版ISSN:1683-8602
  • 出版年度:2014
  • 卷号:12
  • 期号:4
  • 页码:755-774
  • 出版社:Tingmao Publish Company
  • 摘要:Ranked set sampling and some of its variants have been applied successfully in different areas of applications such as industrial statistics, economics, environmental and ecological studies, biostatistics, and statistical genetics. Ranked set sampling is a sampling method that more efficient than simple random sampling. Also, it is well known that Fisher information of a ranked set sample (RSS) is larger than Fisher information of a simple random sample (SRS) of the same size about the unknown parameter of the underlying distribution in parametric inference. In this paper, we consider the Farlie-Gumbel-Morgenstern (FGM) family and study the information measures such as Shannon’s entropy, Rényi entropy, mutual information, and Kullback-Leibler (KL) information of RSS data. Also, we investigate their properties and compare them with a SRS data.
  • 关键词:Concomitants of order statistics; Farlie-Gumbel-Morgenstern (FGM) family; Rényi entropy; Shannon entropy; Ranked set sampling.
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