The refinement of PLS models by iterative weighting of predictor variables and objects

Chemometrics and Intelligent Laboratory Systems

Volumn 68, Issue 1-2, 2003, Pages 29-40

  Forina, Michele ^a   Casolino, Chiara ^a   Almansa, Eva M ^b  

^a UNIVERSITY OF GENOA   (Italy)

^b UNIVERSITY OF GRANADA   (Spain)

Author keywords

Multivariate regression; Outliers; Partial least squares; Robust regression

Indexed keywords

ALGORITHM; CONFERENCE PAPER; INTERMETHOD COMPARISON; PREDICTION; PRIORITY JOURNAL; REGRESSION ANALYSIS; STATISTICAL MODEL; WEIGHT;

EID: 0041326475     PISSN: 01697439     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0169-7439(03)00085-6     Document Type: Conference Paper

References (19)

1. Lucasius C.B., Kateman G. Genetic algorithm for large-scale optimization in chemometrics: an application. Trends Anal. Chem. 10:1991;254-281.
2. Martens H., Naes T. Multivariate Calibration. 1989;Wiley, Chichester.
3. Frank I.E. Intermediate least squares regression method. Chemom. Intell. Lab. Syst. 1:1987;233-242.
4. Kettaneh-Wold N., MacGregor J.F., Wold S. Multivariate design of process experiments (M-DOPE). Chemom. Intell. Lab. Syst. 23:1994;39-50.
5. Lindgren F., Geladi P., Rannar S., Wold S. Interactive Variable Selection (IVS) for PLS. Part 1: theory and algorithms. J. Chemom. 8:1994;349.
6. Forina M., Drava G., De La Pezuela C. Automatic selection of predictors in PLS by means of statistical test on the correlation coefficient of the marginal least-squares regressions. VI CAC (Chemometrics in Analytical Chemistry Conference), Tarragona (Spain), June, 25-29:1986;. Abstract Book, PII-29.
7. Garido Frenich A., Jouan-Rimbaud D., Massart D.L., Kuttatharmmakul S., Martinez Galera M., Martinez Vidal J.L. Wavelength selection method for multicomponent spectrophotometric determination using partial least squares. Analyst. 120:1995;2787-2792.
8. Boggia R., Forina M., Fossa P., Mosti L. Chemometrics study and validation strategies in the structure-activity relationships of a new class of cardiotonic agents. Quant. Struct.-Act. Relatsh. (QSAR). 16:1997;201-213.
9. The Unscrambler®, Camo Asa, Oslo.
10. Centner V., Massart D.L., de Noord O.E., de Jong S., Vandeginste B.M., Sterna C. Elimination of uninformative variables for multivariate calibration. Anal. Chem. 68:1996;3851-3858.
11. Forina M., Casolino C., Pizarro Millan C. Iterative Predictor Weighting PLS (IPW): a technique for the elimination of useless predictors in regression problems. J. Chemom. 13:1999;165-184.
12. Wakeling I.N., Macfie H.J.H. A robust PLS procedure. J. Chemom. 6:1992;189-198.
13. Cummins D.J., Andrews C.W. Iteratively reweighted partial least squares: a performance analysis by Montecarlo simulation. J. Chemom. 9:1995;489-507.
14. Forina M., Drava G.et al. Transfer of calibration function in near-infrared spectroscopy. Chemom. Intell. Lab. Syst. 27:1995;189-203.
15. M. Forina, S. Lanteri, C. Armanino, Q-PARVUS Release 3.0, An extendable package of programs for explorative data analysis, classification and regression analysis, Dip. Chimica e Tecnologie Farmaceutiche, University of Genova, free available at http://parvus.unige.it.
16. Forina M., Casolino C. Joint PLS regression model for two instruments. 8th International Conference on Near-Infrared Spectroscopy, Essen, September 15-19:1997.
17. Thomas E., Haaland D. Anal. Chem. 62:1990;1091.
18. Osten D. J. Chemom. 2:1988;39.
19. van der Voet H. Chemolab. 25:1994;313-323.