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  • 标题:Some Tests Concerning the Covariance Matrix in High Dimensional Data
  • 本地全文:下载
  • 作者:Muni S. Srivastava
  • 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:2005
  • 卷号:35
  • 期号:2
  • 页码:251-272
  • DOI:10.14490/jjss.35.251
  • 出版社:JAPAN STATISTICAL SOCIETY
  • 摘要:

    In this paper, tests are developed for testing certain hypotheses on the covariance matrix Σ, when the sample size N = n + 1 is smaller than the dimension p of the data. Under the condition that (tr Σ i ⁄ p ) exists and > 0, as p → ∞, i =1,…,8, tests are developed for testing the hypotheses that the covariance matrix in a normally distributed data is an identity matrix, a constant time the identity matrix (spherecity), and is a diagonal matrix. The asymptotic null and non-null distributions of these test statistics are given.

  • 关键词:asymptotic distributions; multivariate normal; null and non-null distributions; sample size smaller than the dimension
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