Variable Selection

Comprehensive Chemometrics

Volumn 3, Issue , 2009, Pages 233-283

  Galvao R K H ^a   Araujo M C U ^b  

^a INSTITUTO TECNOLÓGICO DE AERONÁUTICA   (Brazil)

^b FEDERAL UNIVERSITY OF PARAÍBA   (Brazil)

Author keywords

Genetic algorithm; Linear regression; Multicollinearity; Multivariate calibration; Quantitative structure activity relationship; Stepwise regression; Successive projections algorithm; Variable selection

Indexed keywords

EID: 84882465645     PISSN: None     EISSN: None     Source Type: Book    
DOI: 10.1016/B978-044452701-1.00075-2     Document Type: Chapter

References (55)

1. Wold S., Sjostrom M., Eriksson L. PLS-Regression: A Basic Tool of Chemometrics. Chemom. Intell. Lab. Syst. 2001, 58:109-130.
2. Draper N.R., Smith H. Applied Regression Analysis 1998, Wiley & Sons, New York. 3rd ed.
3. Gusnanto A., Pawitan Y., Huang J., Lane B. Variable Selection in Random Calibration of Near-Infrared Instruments: Ridge Regression and Partial Least Squares Regression Settings. J. Chemom. 2003, 17:174-185.
4. Martens H., Naes T. Multivariate Calibration 1993, Wiley & Sons, London, NY.
5. Massart D.L., Vandeginste B.G.M., Buydens L.M.C., De Jong S., Lewi P.J., Smeyers-Verbeke J. Handbook of Chemometrics and Qualimetrics 1997, Elsevier, Amsterdam.
6. Spiegelman C.H., McShane M.J., Goetz M.J., Motamedi M., Yue Q.L., Coté G.L. Theoretical Justification of Wavelengh Selection in PLS Calibration: Development of a New Algorithm. Anal. Chem. 1998, 70:35-44.
7. Goicoechea H.C., Olivieri A.C. A New Family of Genetic Algorithms for Wavelengh Intervals Selection in Multivariate Analytical Spectroscopy. J. Chemom. 2003, 17:338-345.
8. Leardi R., Seasholtz M.B., Pell R.J. Variable Selection for Multivariate Calibration Using a Genetic Algorithm: Prediction of Additive Concentrations in Polymer Films from Transform-Infrared Spectral Data. Anal. Chim. Acta 2002, 461:189-200.
9. Beebe K.R., Pell R.J., Seasholtz M.B. Chemometrics: A Pratical Guide 1998, Wiley & Sons, New York.
10. Kohavi R., John G.H. Wrappers for Feature Subset Selection. Artif. Intell. 1997, 97:273-324.
11. Matlab 6.5 User's Guide; The Mathworks: Natick, MA, USA.
12. Ditusa M.R., Schilt A.A. Selection of Wavelengths for Optimum Precision in Simultaneous Spectrophotometric Determinations. J. Chem. Educ. 1985, 62:541-542.
13. Naes T., Isaksson T., Fearn T., Davies T. A User-Friendly Guide to Multivariate Calibration and Classification 2002, NIR Publications, Chichester.
14. Rossi F., François D., Wertz V., Meurens M., Verleysen M. Fast Selection of Spectral Variables with B-Spline Compression. Chemom. Intell. Lab. Syst. 2007, 86:208-218.
15. Rossi F., Lendasse A., François D., Wertz V., Verleysen M. Mutual Information for the Selection of Relevant Variables in Spectrometric Nonlinear Modelling. Chemom. Intell. Lab. Syst. 2006, 80:215-226.
16. Lorber A. Error Propagation and Figures of Merit for Quantification by Solving Matrix Equations. Anal. Chem. 1986, 58:1167-1172.
17. Kalivas J.H., Lang P.M. Interrelationships Between Sensitivity and Selectivity Measures for Spectroscopic Analysis. Chemom. Intell. Lab. Syst. 1996, 32:135-149.
18. Kalivas J.H., Lang P.M. Mathematical Analysis of Spectral Orthogonality 1994, Marcel Dekker, New York.
19. ASTM E 1655-00 (Standard Practices for Infrared Multivariate Quantitative Analysis).
20. Kennard R.W., Stone L.A. Computer Aided Design of Experiments. Technometrics 1969, 11:137-148.
21. Galvão R.K.H., Araújo M.C.U., José G.E., Pontes M.J.C., Silva E.C., Saldanha T.C.B. A Method for Calibration and Validation Subset Partitioning. Talanta 2005, 67:736-740.
22. Mallows C.L. Some Comments on Cp. Technometrics 1973, 15:661-675.
23. Stout F., Baines M.R., Kalivas J.H. Impartial Graphical Comparison of Multivariate Calibration Methods and the Harmony/Parsimony Tradeoff. J. Chemom. 2006, 20:464-475.
24. Norgaard L., Saudland A., Wagner J., Nielsen J.P., Munck L., Engelsen S.B. Interval Partial Least-Squares Regression (iPLS): A Comparative Chemometric Study with an Example from Near-Infrared Spectroscopy. Appl. Spectrosc. 2000, 54:413-419.
25. Centner V., Massart D., Noord O., Jong S., Vandeginste B., Sterna C. Elimination of Uninformative Variables for Multivariate Calibration. Anal. Chem. 1996, 68:3851-3858.
26. Efron B. The Jack-Knife, the Bootstrap and Other Resampling Plans 1982, Society for Industrial and Applied Mathematics, Philadelphia, PA.
27. Martens H., Martens M. Modified Jack-Knife Estimation of Parameter Uncertainty in Bilinear Modelling by Partial Least Squares Regression (PLSR). Food Qual. Prefer. 2000, 11:5-16.
28. Faber K., Kowalski B.R. Propagation of Measurement Errors for the Validation of Predictions Obtained by Principal Component Regression and Partial Least Squares. J. Chemom. 1997, 11:181-238.
29. Nelder J.A., Mead R. A Simplex Method for Function Minimization. Comput. J. 1965, 7:308-313.
30. Gill P.E., Murray W., Wright M.H. Practical Optimization 1981, Academic Press, London.
31. Bohachevsky O., Johnson M.E., Stein M.L. Generalized Simulated Annealing for Function Optimization. Technometrics 1986, 28:209-217.
32. Kalivas J.H., Roberts N., Sutter J.M. Global Optimization by Simulated Annealing with Wavelength Selection for Ultraviolet-Visible Spectrophotometry. Anal. Chem. 1989, 61:2024-2030.
33. Goldberg D.E. Genetic Algorithms in Search, Optimization, and Machine Learning 1989, Addison-Wesley, Reading, MA.
34. Fogel D.B. Evolutionary Computation 1995, IEEE Press, New York.
35. Jouan-Rimbaud D., Massart D.L., Leardi R., Noord O.E. Genetic Algorithms as a Tool for Wavelength Selection in Multivariate Calibration. Anal. Chem. 1995, 67:4295-4301.
36. Leardi R. Genetic Algorithms in Chemometrics and Chemistry: A Review. J. Chemom. 2001, 15:559-569.
37. Todeschini R., Galvagni D., Vílchez J.L., del Olmo M., Navas N. Kohonen Artificial Neural Networks as a Tool for Wavelengh Selection in Multicomponent Spectrofluorimetric PLS Modelling: Application to Phenol, o-Cresol, m-Cresol and p-Cresol Mixtures. Trends Anal. Chem. 1999, 18:93-98.
38. Araújo M.C.U., Saldanha T.C.B., Galvão R.K.H., Yoneyama T., Chame H.C., Visani V. The Sucessive Projections Algorithm for Variable Selection in Spectroscopic Multicomponent Analysis. Chemom. Intell. Lab. Syst. 2001, 57:65-73.
39. Galvão R.K.H., Pimentel M.F., Araújo M.C.U., Yoneyama T., Visani V. Aspect of the Successive Projections Algorithm for Variable Selection in Multivariation Calibration Applied to Plasma Emission Spectrometry. Anal. Chim. Acta 2001, 443:107-115.
40. Breitkreitz M.C., Raimundo I.M., Rohwedder J.J.R., Pasquini C., Dantas Filho H.A., José G.E., Araújo M.C.U. Determination of Total Sulphur in Diesel Fuel Employing NIR Spectroscopy and Multivariate Calibration. Analyst 2003, 128:1204-1207.
41. Galvão R.K.H., Araújo M.C.U., Fragoso W.D., Silva E.C., José G.E., Soares S.F.C., Paiva H.M. A Variable Elimination Method to Improve the Parsimony of MLR Models Using the Successive Projections Algorithm. Chemom. Intell. Lab. Syst. 2008, 92:83-91.
42. Galvão R.K.H., Araújo M.C.U., Silva E.C., José G.E., Soares S.F.C., Paiva H.M. Cross-Validation for the Selection of Spectral Variables Using the Successive Projections Algorithm. J. Braz. Chem. Soc. 2007, 18:1580-1584.
43. Haaland D.M., Thomas E.V. Partial Least-Squares Methods for Spectral Analyses. 1. Relation to Other Quantitative Calibration Methods and the Extraction of Qualitative Information. Anal. Chem. 1988, 60:1193-1202.
44. Li B.X., Wang D.L., Xu C.L., Zhang Z.J. Flow-Injection Simultaneous Chemiluminescence Determination of Ascorbic Acid and l-Cysteine with Partial Least Squares Calibration. Mikrochim. Acta 2005, 149:205-212.
45. Pereira A.F.C., Pontes M.J.C., Gambarra Neto F.F., Santos S.R.B., Galvão R.K.H., Araújo M.C.U. NIR Spectrometric Determination of Quality Parameters in Vegetable Oils Using iPLS and Variable Selection. Food Res. Int. 2008, 41:341-348.
46. Hendriks M.M.W.B., de Boer J.H., Smilde A.K., Doornbos D.A. Multicriteria Decision Making. Chemom. Intell. Lab. Syst. 1992, 16:175-191.
47. Wienke D., Lucasius C., Kateman G. Multicriteria Target Vector Optimization of Analytical Procedures Using a Genetic Algorithm. Part I. Theory, Numerical Simulations and Application to Atomic Emission Spectroscopy. Anal. Chim. Acta 1992, 265:211-225.
48. Dietz A., Azzaro-Pantel C., Pibouleau L., Domenech S. Multiobjective Optimization for Multiproduct Batch Plant Design Under Economic and Environmental Considerations. Comput. Chem. Eng. 2006, 30:599-613.
49. Halsall-Whitney H., Thibault J. Multi-Objective Optimization for Chemical Processes and Controller Design: Approximating and Classifying the Pareto Domain. Comput. Chem. Eng. 2006, 30:1155-1168.
50. Hansen C. Rank-Deficient and Discrete Ill-Posed Problems 1998, Society for Industrial and Applied Mathematics, Philadelphia, PA.
51. Kalivas J.H. Pareto Calibration with Built-In Wavelength Selection. Anal. Chim. Acta 2004, 505:9-14.
52. Stout F., Kalivas J.H., Héberger K. Wavelength Selection for Multivariate Calibration Using Tikhonov Regularization. Appl. Spectrosc. 2007, 61:85-95.
53. Tibshirani R. Regression Shrinkage and Selection via the Lasso. J. R. Stat. Soc. Ser. B 1996, 58:267-288.
54. Selwood D.L., Livingstone D.J., Comley J.C.W., O'Dowd A.B., Hudson A.T., Jackson P., Jandu K.S., Rose V.S., Stables J.N. Structure-Activity Relationships of Antifilarial Antimycin Analogs: A Multivariate Pattern Recognition Study. J. Med. Chem. 1990, 33:136-142.
55. Walczak B. Wavelets in Chemistry 2000, Elsevier Science, New York.