logo_2Cy.gif
Home About us Media Research Consultancy Training Site map Contact

Home » Links and downloads » Papers » Component selection

  • M.C. Denham
    Choosing the number of factors in partial least squares regression: estimating and minimizing the mean squared error of prediction
    Journal of Chemometrics, 14 (2000) 351-361
    Abstract
  • S.Z. Fairchild and J.H. Kalivas
    PCR eigenvector selection based on correlation relative standard deviations
    Journal of Chemometrics, 15 (2001) 615-625
    Abstract; request
  • S. Gourvénec, J.A. Fernández Pierna, D.L. Massart and D.N. Rutledge
    An evaluation of the PoLiSh smoothed regression and the Monte Carlo cross-validation for the determination of the complexity of a PLS model
    Chemometrics and Intelligent Laboratory Systems, 68 (2003) 41-51
    Abstract; request
  • R.L. Green and J.H. Kalivas
    Graphical diagnostics for regression model determinations with consideration of the bias/variance trade-off
    Chemometrics and Intelligent Laboratory Systems, 60 (2002) 173-188
    Abstract; request
  • J.T. Hwang and D. Nettleton
    Principal component regression with data-chosen components and related methods
    Technometrics, 45 (2003) 70-79
    Abstract
  • S. Ledauphin, M. Hanafi and E.M. Qannari
    Simplification and signification of principal components
    Chemometrics and Intelligent Laboratory Systems, 74 (2004) 277-281
    Abstract
  • D.N. Rutledge, A. Barros and I. Delgadillo
    PoLiSh—smoothed partial least-squares regression
    Analytica Chimica Acta, 446 (2001) 281-296
    Abstract; request
  • H. Seipel and J.H. Kalivas
    Effective rank for multivariate calibration methods
    Journal of Chemometrics, 18 (2004) 306-311
    Abstract; request
  • J.M. Sutter, J.H. Kalivas and P.M. Lang
    Which principal components to utilize for principal component regression
    Journal of Chemometrics, 6 (1992) 217-225
    Abstract; request
  • E.V. Thomas
    Non-parametric statistical methods for multivariate calibration model selection and comparison
    Journal of Chemometrics, 17 (2003) 653-659
    Abstract
  • H. van der Voet
    Comparing the predictive accuracy of models using a simple randomization test
    Chemometrics and Intelligent Laboratory Systems, 25 (1994) 313-323
    Abstract; request
  • I.N. Wakeling and J.J. Morris
    A test of significance for partial least squares regression
    Journal of Chemometrics, 7 (1993) 291-304
    Abstract
  • Q.-S. Xu and Y.-Z. Liang
    Monte Carlo cross validation
    Chemometrics and Intelligent Laboratory Systems, 56 (2001) 1-11
    Abstract
  • Q.-S. Xu, Y.-Z. Liang and Y.-P. Du
    Monte Carlo cross-validation for selecting a model and estimating the prediction error in multivariate calibration
    Journal of Chemometrics, 18 (2004) 112-120
    Abstract