An evaluation of the PoLiSh smoothed regression and the Monte Carlo Cross-Validation for the determination of the complexity of a PLS model
作者： S Gourvénec , J.A Fernández Pierna , D.L Massart , D.N Rutledge
DOI: 10.1016/S0169-7439(03)00086-8
关键词:
摘要: Abstract A crucial point of the PLS algorithm is selection right number factors or components (i.e., determination optimal complexity system to avoid overfitting). The leave-one-out cross-validation usually used determine a model, but in practice, it found that often too many are retained with this method. In study, Monte Carlo Cross-Validation (MCCV) and PoLiSh smoothed regression compared better known adjusted Wold's R criterion.
elsevier.com
sci-hub.se 参考文章(15)
Qing-Song Xu, Yi-Zeng Liang, Monte Carlo cross validation Chemometrics and Intelligent Laboratory Systems. ,vol. 56, pp. 1- 11 ,(2001) , 10.1016/S0169-7439(00)00122-2
David M. Haaland, Edward V. Thomas, Partial least-squares methods for spectral analyses. 1. Relation to other quantitative calibration methods and the extraction of qualitative information Analytical Chemistry. ,vol. 60, pp. 1193- 1202 ,(1988) , 10.1021/AC00162A020
John H. Kalivas, Two data sets of near infrared spectra Chemometrics and Intelligent Laboratory Systems. ,vol. 37, pp. 255- 259 ,(1997) , 10.1016/S0169-7439(97)00038-5
Jun Shao, Linear Model Selection by Cross-validation Journal of the American Statistical Association. ,vol. 88, pp. 486- 494 ,(1993) , 10.1080/01621459.1993.10476299
Norman Richard Draper, Harry Smith, Applied Regression Analysis ,(1966)
Douglas N. Rutledge, António Barros, Ivonne Delgadillo, PoLiSh — smoothed partial least-squares regression Analytica Chimica Acta. ,vol. 446, pp. 279- 294 ,(2001) , 10.1016/S0003-2670(01)01269-7
David M. Haaland, Edward V. Thomas, Partial least-squares methods for spectral analyses. 2. Application to simulated and glass spectral data Analytical Chemistry. ,vol. 60, pp. 1202- 1208 ,(1988) , 10.1021/AC00162A021
I Ruisánchez, F.X Rius, S Maspoch, J Coello, T Azzouz, R Tauler, L Sarabia, M.C Ortiz, J.A Fernández, D Massart, A Puigdomènech, C Garcı́a, Preliminary results of an interlaboratory study of chemometric software and methods on NIR data. Predicting the content of crude protein and water in forages Chemometrics and Intelligent Laboratory Systems. ,vol. 63, pp. 93- 105 ,(2002) , 10.1016/S0169-7439(02)00039-4
V. Centner, O.E. de Noord, D.L. Massart, Detection of nonlinearity in multivariate calibration Analytica Chimica Acta. ,vol. 376, pp. 153- 168 ,(1998) , 10.1016/S0003-2670(98)00543-1
Richard R. Picard, R. Dennis Cook, Cross-Validation of Regression Models Journal of the American Statistical Association. ,vol. 79, pp. 575- 583 ,(1984) , 10.1080/01621459.1984.10478083