References

Tutorials:

  1. P.J. Rousseeuw, M. Debruyne, S. Engelen, M. Hubert, Robustness and outlier detection in chemometrics, Critical Reviews in Analytical Chemistry 36 (2006) 221-242
  2. Y.-Z. Liang, O.M. Kvalheim, Robust methods for multivariate analysis - a tutorial review, Chemometrics and Intelligent Laboratory Systems 32 (1996) 1-10
  3. S. Frosch Moller, J. von Frese, R. Bro, Robust methods for multivariate data analysis, Journal of Chemometrics 19 (2005) 549-563
  4. M. Daszykowski, K. Kaczmarek, Y. Vander Heyden, B. Walczak, Robust statistics in data analysis - a review. Basic concepts, Chemometrics and Intelligent Laboratory Systems 85 (2007) 203-219
Papers and books:
  1. E.R. Malinowski, Factor analysis in chemistry, John Wiley & Sons, INC., New York, 1991
  2. H. Martens, T. Naes, Mutivariate Calibration, John Wiley & Sons, Chichester, UK, 1989
  3. T. Naes, T. Isaksson, T. Fearn, T. Davis, Multivariate calibration and classification, NIR Publications, Chichester, UK, 2002
  4. P.J. Rousseeuw, A.M. Leroy, Robust regression and outlier detection, John Wiley & Sons, New York, 1987
  5. P.J. Rousseeuw, B. van Zomeren, Journal of the American Statistical Association 85 (1990) 633-651
  6. P.J. Huber, Robust statistics, Wiley, New York, 1981
  7. M. Hubert, P. J. Rousseeuw, S. Verboven, A fast method for robust principal components with applications to chemometrics, Chemometrics and Intelligent Laboratory Systems 60 (2002) 101-111
  8. C. Croux, G. Haesbroeck, Principal component analysis based on robust estimators of the covariance or correlation matrix: influence function and efficiencies, Biometrika 87 (2000) 603-618
  9. H. Hove, Y.-Z. Liang, O.M. Kvalheim, Trimmed object projection: a nonparametric latent-structure decomposition method, Chemometrics and Intelligent Laboratory Systems 27 (1995) 33-40
  10. B. Walczak, D.L. Massart, Robust principal components regression as a detection tool for outliers, Chemometrics and Intelligent Laboratory Systems 27 (1995) 41-54
  11. M. Hubert, S. Verboven, A robust PCR method for high-dimensional regressors, Journal of Chemometrics 17 (2003) 438-452
  12. M. Hubert, K. Vanden Branden, Robust methods for partial least squares regression, Journal of Chemometrics 17 (2003) 537-549
  13. S. Serneels, C. Croux, P. Filzmoser, P. J. Van Espen, Partial Robust M-regression, Chemometrics and Intelligent Laboratory Systems 79 (2005) 55-64
  14. S. Verboven, M. Hubert, LIBRA: a MATLAB library for robust analysis, Chemometrics and Intelligent Laboratory Systems 75 (2005) 127-136
  15. R.J. Barnes, M.S. Dhanoa, S.J. Lister, Standard Normal Variate Transformation and De-trending of Near-Infrared Diffuse Reflectance Spectra, Applied Spectroscopy 43 (1989) 772-777
  16. P.J. Rousseeuw, C. Croux, Alternatives to the median absolute deviation, J. Am. Statist. Assoc. 88 (1993) 1273-1283
  17. W. Wu, D.L. Massart, S. de Jong, The kernel PCA algorithms for wide data. Part I: Theory and algorithms, Chemometrics and Intelligent Laboratory Systems 36 (1997) 165-172
  18. C. Croux, A. Ruiz-Gazen, High breakdown estimators for principal components: the projection-pursuit approach revisited, Journal of Multivariate Analysis 95 (2005) 206-226
  19. S. de Jong, SIMPLS: An alternative approach to partial least squares regression, Chemometrics and Intelligent Laboratory Systems 18 (1993) 251-263
  20. M. Stone, R.J. Brooks, Continuum regression: cross-validated sequentially constructed prediction embracing ordinary least squares, partial least squares and principal component regression, Journal of the Royal Statistical Society B 5 (1984) 237-269
  21. S. de Jong, R.W. Farebrother, Extending the relationship between ridge regression and continuum regression, Chemometrics and Intelligent Laboratory Systems 25 (1994) 179-181
  22. S. Serneels, P. Filzmoser, C. Croux, P.J. Van Espen, Robust Continuum Regression, Chemometrics and Intelligent Laboratory Systems 76 (2005) 197-204
  23. Q.-S. Xu, Y.-Z. Liang, Monte Carlo cross validation, Chemometrics and Intelligent Laboratory Systems 56 (2001) 1-11
  24. K. Baumann, H. Albert, M. von Korff, A systematic evaluation of the benefits and hazards of variable selection in latent variable regression. Part I. Search algorithm, theory and simulations, Journal of Chemometrics 16 (2002) 339-350
  25. B. Walczak, D.L. Massart, The Radial Basis Functions - Partial Least Squares approach as a flexible non-linear regression technique, Analytica Chimica Acta 331 (1996) 177-185
  26. B. Walczak, D.L. Massart, Application of Radial Basis Functions - Partial Least Squares to non-linear pattern recognition problems: diagnosis of process faults, Analytica Chimica Acta 331 (1996) 187-193
  27. R.W. Kennard, L.A. Stone, Computer aided design of experiments, Technometrics 11 (1969) 137-148
  28. O. Hossjer, C. Croux, Generalizing Univariate Signed Rank Statistics for Testing and Estimating a Multivariate Location Parameter, Non-parametric Statistics 4 (1995) 293-308

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