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Volumn 97, Issue 4, 2006, Pages 827-843

A high-dimensional test for the equality of the smallest eigenvalues of a covariance matrix

Author keywords

Principal components analysis; Sums of eigenvalues

Indexed keywords


EID: 27944490752     PISSN: 0047259X     EISSN: 10957243     Source Type: Journal    
DOI: 10.1016/j.jmva.2005.05.003     Document Type: Article
Times cited : (52)

References (13)
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  • 3
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    • On Wielandt's inequality and its application to the asymptotic distribution of the eigenvalues of a random symmetric matrix
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    • (1991) Ann. Statist. , vol.19 , pp. 260-271
    • Eaton, M.L.1    Tyler, D.E.2
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    • Tests of significance for latent roots of covariance and correlation matrices
    • D.N. Lawley Tests of significance for latent roots of covariance and correlation matrices Biometrika 43 1956 128-136
    • (1956) Biometrika , vol.43 , pp. 128-136
    • Lawley, D.N.1
  • 6
    • 0036392431 scopus 로고    scopus 로고
    • Some hypothesis tests for the covariance matrix when the dimension is large compared to the sample size
    • O. Ledoit M. Wolf Some hypothesis tests for the covariance matrix when the dimension is large compared to the sample size Ann. Statist. 30 2002 1081-1102
    • (2002) Ann. Statist. , vol.30 , pp. 1081-1102
    • Ledoit, O.1    Wolf, M.2
  • 7
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    • Smith, R.L.1
  • 12
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    • An extremum property of sums of eigenvalues
    • H. Wielandt An extremum property of sums of eigenvalues Proc. Amer. Math. Soc. 6 1995 106-110
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    • Wielandt, H.1
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    • On the limit of the largest eigenvalue of the large dimensional sample covariance matrix, Probab
    • Y.Q. Yin Z.D. Bai P.R. Krishnaiah On the limit of the largest eigenvalue of the large dimensional sample covariance matrix Probab. Theory Related Fields 78 1988 509-521
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.