Partial least squares for discrimination

Journal of Chemometrics

Volumn 17, Issue 3, 2003, Pages 166-173

  Barker, Matthew ^a   Rayens, William ^b  

^a PROCTER AND GAMBLE COMPANY   (United States)

^b UNIVERSITY OF KENTUCKY   (United States)

Author keywords

Dimension reduction; Linear discrimination; Partial least squares

Indexed keywords

DISCRIMINANT ANALYSIS;

CANONICAL CORRELATIONS ANALYSIS; DIMENSION REDUCTION; GROUP STRUCTURE; LEAST SQUARE CORRELATION ANALYSIS; LINEAR DISCRIMINANT ANALYZE; LINEAR DISCRIMINATION; PARTIAL LEAST-SQUARES; REGRESSION PROBLEM;

LEAST SQUARES APPROXIMATIONS;

ALGORITHM; ARTICLE; CORRELATION ANALYSIS; PARTIAL LEAST SQUARES; REGRESSION ANALYSIS; STATISTICAL ANALYSIS; STATISTICAL PARAMETERS;

EID: 0037350844     PISSN: 08869383     EISSN: None     Source Type: Journal    
DOI: 10.1002/cem.785     Document Type: Article

References (30)

1. Gottfries J, Blennow K, Wallin A and Gottfries CG. Diagnosis of dementias using partial least squares discriminant analysis. Dementia 1995; 6: 83-88.
2. Briandet R, Kemsley E and Wilson R. Discrimination of Arabica and Robusta in instant coffee by Fourier transform infrared spectroscopy and chemometrics. J. Agric. Food Chem. 1996; 44: 170-174.
3. Saaksjarvi E, Khalighi M and Minkkinen P. Waste water pollution modelling in the southern area of Lake Saimaa, Finland, by the SIMCA pattern recognition method. Chemometrics Intell. Lab. Syst. 1989; 7: 171-180.
4. Berntsson P and Wold S. Comparison between x-ray crystallographic data and physicochemical parameters with respect to their information about the calcium channel antagonist activity of 4-phenyl-1,4-dihydropyridines. Quant. Struct.-Activ. Relat. 1986; 5: 45-50.
5. Delwiche S, Chen Y-R and Hruschka W. Differentiation of hard red wheat by near-infrared analysis of bulk samples. Grain Qual. 1972; 3: 243-247.
6. Sundbom E, Bodlund O and Hojerback T. Object relation and defensive operations in transsexuals and borderline patients as measured by the Defense Mechanism Test. Nordic J. Psychiatry 1995; 49: 379-388.
7. Ortiz M, Sarabia L, Symington C, Santamaria F and Iniguez M. Analysis of ageing and typification of vintage ports by partial least squares and soft independent modelling class analogy. Analyst 1996; 121: 1009-1013.
8. Iizuka K and Aishima T. Soy sauce classification by geographic region based on NIR spectra and chemometrics pattern recognition. J. Food Sci. 1997; 62: 101-104.
9. Vong R, Geladi P, Wold S and Esbensen K. Source contributions to ambient aerosol calculated by discriminant partial least squares regression. J. Chemometrics 1988; 2: 281-296.
10. Geladi P and Kowalski B. Partial least squares regression: a tutorial. Anal. Chim. Acta 1986; 185: 1-17.
11. Helland IS. On the structure of partial least squares regression. Commun. Statist. B - Simul. Comput. 1988; 17: 581-607.
12. Helland IS. Maximum likelihood regression on relevant components. J. R. Statist. Soc. B 1992; 54: 637-645.
13. Hoskuldsson A. PLS regression methods. J. Chemometrics 1988; 2: 211-228.
14. Kettaneh-Wold N. Analysis of mixture data with partial least squares. Chemometrics Intell. Lab. Syst. 1992; 14: 57-69.
15. Wold H. Estimation of principal components and related models by iterative least squares. In Multivariate Analysis, Krishnaiah PR (ed.). Academic Press: New York, 1966; 391-420.
16. Wold H. Soft modeling: the basic design and some extensions. In Systems under Indirect Observation, Causality-Structure-Prediction, Joreskog KG, Wold H (eds). North-Holland: Amsterdam, 1981; 1-54.
17. Wold S, Martens H and Wold H. The multivariate calibration problem in chemistry solved by the PLS method. In Proceedings from the Conference on Matrix Pencils, Ruhe A, Kagstrom B (eds). Springer: Heidelberg, 1983; 286-298.
18. Barker M. Partial least squares for discrimination. PhD Dissertation, University of Kentucky, 2000.
19. Frank I and Friedman J. A statistical view of some chemometrics regression tools. Technometrics 1993; 35: 109-148.
20. Hinkle J and Rayens WS. Partial least squares and compositional data: problems and alternatives. Chemometrics Intell. Lab. Syst. 1995; 30: 159-172.
21. Hinkle J and Rayens WS. Partial least squares, reciprocal components and reciprocal curves. Proceedings from the 1998 Joint Statistical Meetings, Dallas, TX, 1998; 126-130.
22. Stone M and Brooks RJ. Continuum regression: cross-validated sequentially constructed prediction embracing ordinary least squares, partial least squares, and principal component regression. J. R. Statist. Soc. B 1990; 52: 237-269.
23. Hinkle J. Reciprocal components, reciprocal curves, and partial least squares. PhD Dissertation, University of Kentucky, 1995.
24. Fisher RA. The use of multiple measurement in taxonomic problems. Ann. Eugen. 1936; 7: 179-188.
25. Kshiragar AM and Arseven E. A note on the equivalency of two discrimination procedures. Am. Statist. 1975; 29: 38-39.
26. Bartlett MS. Further aspects of the theory of multiple regression. Proc. Camb. Philos. Soc. 1938; 34: 33-40.
27. McLachlan GJ. Discriminant Analysis and Statistical Pattern Recognition. Wiley: New York, 1992.
28. Lachenbruch PA and Mickey MR. Estimation of error rates in discriminant analysis. Technometrics 1968; 10: 1-11.
29. Rayens WS and Andersen A. Oriented partial least squares. Ital. J. Appl. Statist. 2003.
30. Rayens WS. The art of maximizing covariance. University of Kentucky Technical Report 383, 2000.