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Volumn 47, Issue 4, 1998, Pages 527-542

Exact principal component influence measures applied to the analysis of spectroscopic data on rice

Author keywords

Chemometrics; Classification; Influence; Principal components; Spectroscopy

Indexed keywords


EID: 0041192910     PISSN: 00359254     EISSN: None     Source Type: Journal    
DOI: 10.1111/1467-9876.00126     Document Type: Article
Times cited : (14)

References (17)
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    • Fearn, T.1
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    • Gnanadesikan, R.1    Kettenring, J.R.2
  • 8
    • 21844512674 scopus 로고
    • Discriminant analysis with singular covariance matrices: Methods and applications to spectroscopic data
    • Krzanowski, W. J., Jonathan, P., McCarthy, W. V. and Thomas, M. R. (1995) Discriminant analysis with singular covariance matrices: methods and applications to spectroscopic data. Appl. Statist., 44, 101-115.
    • (1995) Appl. Statist. , vol.44 , pp. 101-115
    • Krzanowski, W.J.1    Jonathan, P.2    McCarthy, W.V.3    Thomas, M.R.4
  • 11
    • 37049070083 scopus 로고
    • Principal component outlier detection and SIMCA: A synthesis
    • Mertens, B., Fearn, T. and Thompson, M. (1994) Principal component outlier detection and SIMCA: a synthesis. Analyst, 119, 2777-2784.
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    • Mertens, B.1    Fearn, T.2    Thompson, M.3
  • 12
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    • _ (1995) The efficient cross-validation of principal components applied to principal component regression. Statist. Comput., 5, 227-235.
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    • Influential observations in principal component analysis: A case study
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    • (1988) J. Appl. Statist. , vol.15 , pp. 39-52
    • Pack, P.1    Jolliffe, I.T.2    Morgan, B.J.T.3
  • 15
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    • Continuum regression: Cross-validated sequentially constructed prediction embracing ordinary least squares, partial least squares and principal components regression
    • Stone, M. and Brooks, R. J. (1990) Continuum regression: cross-validated sequentially constructed prediction embracing ordinary least squares, partial least squares and principal components regression (with discussion). J. R. Statist. Soc. B, 52, 237-269.
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    • Stone, M.1    Brooks, R.J.2
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    • Effects on the eigenstructure of a data matrix when deleting an observation
    • Wang, S. G. and Nyquist, H. (1991) Effects on the eigenstructure of a data matrix when deleting an observation. Comput. Statist. Data Anal., 11, 179-188.
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    • Wang, S.G.1    Nyquist, H.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.