Skip to main content

The multivariate calibration problem in chemistry solved by the PLS method

Section C Generalized Singular Values And Data Analysis

Part of the Lecture Notes in Mathematics book series (LNM,volume 973)

Keywords

  • Partial Little Square
  • Conjugate Gradient Method
  • Ridge Regression
  • Partial Little Square Model
  • Principal Component Regression

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

This is a preview of subscription content, access via your institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (Canada)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   44.99
Price excludes VAT (Canada)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   59.95
Price excludes VAT (Canada)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  • N.R. DRAPER and H. SMITH (1981). Applied regression analysis, 2.ed. Wiley, New York.

    MATH  Google Scholar 

  • B.R. KOWALSKI (1975). Chemometrics: Views and propositions. J.Chem.Info.Comput. Syst. 15, 201.

    CrossRef  Google Scholar 

  • D.W. MARQUARDT (1970). Generalized inverses, ridge regression, biased linear and non-linear estimation. Technometrics 12, 591–612.

    CrossRef  MATH  Google Scholar 

  • M. STONE (1974). Cross-validatory choice and assessment of statistical predictions. J.Roy.Statist.Soc. B36, 111.

    MathSciNet  MATH  Google Scholar 

  • G. WAHBA (1977). Practical approximate solution to linear operator equations when the data are noisy. SIAM J.Numer.Anal. 14, 651.

    CrossRef  MathSciNet  MATH  Google Scholar 

  • H. WOLD (1982) in Systems under indirect observation. Causality, structure, prediction (K.G. Jöreskog and H. Wold, Ed.s). North-Holland, Amsterdam.

    Google Scholar 

  • S. WOLD (1976). Pattern recognition by means of disjoint principal components models. Pattern Recognition 8, 127.

    CrossRef  MATH  Google Scholar 

  • S. WOLD and M. SJÖSTRÖM (1977). SIMCA, a method for analyzing chemical data in terms of similarity and analogy. In Chemometrics: Theory and application (B.R. Kowalski, Ed.). Amer.Chem.Soc.Symp.Ser. no. 52.

    Google Scholar 

  • S. WOLD (1978). Crossvalidatory estimation of the number of components in factor and principal components analysis. Technometrics 20, 397.

    CrossRef  MATH  Google Scholar 

  • S. WOLD, H. WOLD, W.J. DUNN, A. RUHE (1982). The collinearity problem in linear regression. The partial least squares (PLS) approach to generalized inverses. Report UMINF-83.80, version 3. Umeå University, Dept. Information Processing.

    Google Scholar 

Download references

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and Permissions

Copyright information

© 1983 Springer-Verlag

About this paper

Cite this paper

Wold, S., Martens, H., Wold, H. (1983). The multivariate calibration problem in chemistry solved by the PLS method. In: Kågström, B., Ruhe, A. (eds) Matrix Pencils. Lecture Notes in Mathematics, vol 973. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0062108

Download citation

  • DOI: https://doi.org/10.1007/BFb0062108

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-11983-8

  • Online ISBN: 978-3-540-39447-1

  • eBook Packages: Springer Book Archive