Study on the Application of Supervised Principal Component Regression Procedure to Near-Infrared Spectroscopy Quantitative Analysis

[in Chinese]; [in Chinese]; [in Chinese]; [in Chinese]; [in Chinese]

Journals >Spectroscopy and Spectral Analysis >Volume 29 >Issue 11 >Page 2959 > Article

Spectroscopy and Spectral Analysis
Vol. 29, Issue 11, 2959 (2009)

Study on the Application of Supervised Principal Component Regression Procedure to Near-Infrared Spectroscopy Quantitative Analysis

[in Chinese]^1、2, [in Chinese]¹, [in Chinese]², [in Chinese]³, and [in Chinese]

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¹[in Chinese]

²[in Chinese]

³[in Chinese]

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DOI: Cite this Article

[in Chinese], [in Chinese], [in Chinese], [in Chinese], [in Chinese]. Study on the Application of Supervised Principal Component Regression Procedure to Near-Infrared Spectroscopy Quantitative Analysis[J]. Spectroscopy and Spectral Analysis, 2009, 29(11): 2959 Copy Citation Text

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References

[2] Burns Donald A, Ciurczak Emil W. Handbook of Near-Infrared Analysis. New York: Marcel Dekker Inc., 1992.

[5] Nguyen D V, Rocke D M. Bioinformatics, 2002, 18: 39.

[6] Wold H. Soft Modelling by Latent Variables: The Nonlinear Iterative Partial Least Squares (NIPALS) Approach, in Perspectives in Probability and Statistics, In Honor of Bartlett M S, 1975.

[7] Myers R H. Classical and Modern Regression with Application, Boston, Massachusetts: Duxbury, 1986.

[8] Mardia K, Kent J, Bibby J. Multivariate Analysis, Academic Press, 1979.

[9] Kerr M K, Martin M, Churchill G. A. Journal of Computational Biology, 2000, 7: 819.

[10] Bair E, Hastie T, Paul D, et al. J. Am. Statist Assoc., 2006, 101: 119.

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