APPROXIMATION OF HYPERGEOMETRIC DISTRIBUTIONS BASED ON A NORMALIZING TRANSFORMATION

• Ouchida Seiji

  Obihiro University of Agriculture and Veterinary Medicine graduate school

• Taneichi Nobuhiro

  Obihiro University of Agriculture and Veterinary Medicine graduate school

• Wang Jinfang

  Department of Mathematics and Informatics Chiba University

Bibliographic Information

Other Title

• 正規化変換に基づく超幾何分布の近似
• セイキカ ヘンカン ニ モトヅク チョウキカ ブンプ ノ キンジ

Abstract

Normalizing transformations are useful for obtaining simple and accurate approximations for the distribution of a statistic. In this paper, we derived a normalizing transformation of a random variate which has a hypergeometric distribution based on the normalizing transformations proposed by Konishi (1981,1991) and Taneichi et al. (2002). Further, we compared our method with some standard approximations for the hypergeometric distributions. It turns out that the accuracy of our method is excellent in many situations.

Journal

• Bulletin of the Computational Statistics of Japan

  Bulletin of the Computational Statistics of Japan 16 (2), 125-131, 2004

  Japanese Society of Computational Statistics

Keywords

• Asymptotic normality
• Continuity corrections

Details

• CRID: 1390282679357771264
• NII Article ID: 110001238547
• NII Book ID: AN10195854
• DOI: 10.20551/jscswabun.16.2_125
• ISSN: 21899789
• ISSN: 09148930
• NDL BIB ID: 7127486
• Web Site: http://id.ndl.go.jp/bib/7127486
• Web Site: https://ndlsearch.ndl.go.jp/books/R000000004-I7127486
• Text Lang: ja
• Data Source:
  • JaLC
  • NDL
  • CiNii Articles
• Abstract License Flag: Disallowed