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  • 标题:A POWER APPROXIMATION FOR THE MULTINOMIAL GOODNESS-OF-FIT TEST BASED ON A NORMALIZING TRANSFORMATION
  • 本地全文:下载
  • 作者:Yuri Sekiya ; Nobuhiro Taneichi ; Hideyuki Imai
  • 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:1999
  • 卷号:29
  • 期号:1
  • 页码:79-87
  • DOI:10.14490/jjss1995.29.79
  • 出版社:JAPAN STATISTICAL SOCIETY
  • 摘要:Cressie and Read(1984)introduced the class of multinomial goodness-of-fit statistics, Ra, based on measures of the divergence between discrete distributions. All Ra have the same chi-squared limiting null distribution. The power of Ra is usually approximated by a noncentral chi-squared distribution that is also the same for all a. In this paper, we propose a new approximation of the power of Ra. The new power approximation, NT, is a normal approximation based on a normalizing transformation. The NT approximation is numerically compared with the other approximations. As a result of the comparison, we find that the NT approximation is superior to the other approximations when a=0(the loglikelihood ratio statistic)and is effective when a<0.
  • 关键词:goodness of fit;multinomial distribution;normalizing transformation
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