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  • 标题:SPHERICAL TRAIT IN CORRESPONDENCE ANALYSIS OF ARTIFICIAL DATA
  • 本地全文:下载
  • 作者:Masashi Okamoto ; Hideki Endo
  • 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:1995
  • 卷号:25
  • 期号:2
  • 页码:183-191
  • DOI:10.14490/jjss1995.25.183
  • 出版社:JAPAN STATISTICAL SOCIETY
  • 摘要:Besides the well-known linear or circular trait, the spherical trait is introduced in correspondence analysis of artificial data. Five types of regular polyhedrons are used as the item pattern. The trait always has three dimensions. Furthermore, solid spherical data can be constructed by adding the center and, if necessary, one or more concentric polyhedrons. Then the data set also has a linear trait representing the radius, which may compete with the spherical trait, hindering a few of the largest eigenvalues in reproducing the item pattern faithfully.
  • 关键词:artificial data;circular trait;correspondence analysis;Guttman series;linear trait;solid spherical data;spherical trait
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