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  • 标题:Generalized Variances Ratio Test for Comparing k Covariance Matrices from Dependent Normal Populations
  • 本地全文:下载
  • 作者:Cirillo, Marcelo Angelo ; Ferreira, Daniel Furtado ; Sáfadi, Thelma
  • 期刊名称:Journal of Modern Applied Statistical Methods
  • 出版年度:2010
  • 卷号:9
  • 期号:2
  • 页码:6
  • 出版社:Wayne State University
  • 摘要:New tests based on the ratio of generalized variances are presented to compare covariance matrices from dependent normal populations. Monte Carlo simulation concluded that the tests considered controlled the Type I error, providing empirical probabilities that were consistent with the nominal level stipulated.
  • 关键词:Dependent normal; bootstrap; variances generalized; power; type I error
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