Robust complexity criteria for nonlinear regression in NARX models

IFAC Proceedings Volumes (IFAC-PapersOnline)

Volumn 36, Issue 16, 2003, Pages 79-84

  Brabanter, Jos De ^a   Pelckmans, Kristiaan ^a   Suykens, Johan A K ^a   Moor, Bart De ^a   Vandewalle, Joos ^a  

^a UNIVERSITY OF LEUVEN   (Belgium)

Author keywords

Akaike information criterion (AIC); breakdown point; influence function; nonparametric variance estimator; smoother matrix; weighted LS SVM

Indexed keywords

AKAIKE INFORMATION CRITERION; BREAKDOWN POINTS; INFLUENCE FUNCTIONS; VARIANCE ESTIMATORS; WEIGHTED LS-SVM;

COST FUNCTIONS;

EID: 33644967011     PISSN: 14746670     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1016/S1474-6670(17)34742-0     Document Type: Conference Paper

References (18)

1. H. Akaike Statistical predictor identification Ann. Inst. Statist. Math 22 1973 203 217
2. B. Efron Bootstrap methods: another look at the jackknife Ann. of Statist 7 1 1979 1 26
3. T. Gasser, L. Sroka, and C. Jennen-Steinmetz Residual variance and residual pattern in nonlinear regression Biometrika 73 1986 625 633
4. F.R. Hampel The influence curve and its role in robust estimation J. Am. Statist. Ass 69 1974 383 393
5. E.J Hannon, and B.G. Quinn The determination of the order of autoregression J. Ray. Statist. Soc. Ser B 41 1979 190 195
6. P.J. Huber Robust estimation of a location parameter Ann. Math. Statist 35 1964 73 101
7. C.M. Hurvich, and C.L. Tsai Regression and time series model selection in small samples Biometrika 76 1989 297 307
8. L. Ljung System Identification, Theory for the User 1987 Prentice Hall
9. C.L. Mallows Some comments on Cp Technometrics 15 1973 661 675
10. J.E. Moody The effective number of parameters: An analysis of generalization and regularization in nonlinear learning systems Neural Information Processing Systems 4 1992 Morgan Kaufmann San Mateo CA 847 854
11. M.H. Neumann Fully data-driven nonparametric variance estimators Statistics 25 1994 189 212
12. T. Poggio, and F. Girosi Networks for approximation and learning Proceedings of the IEEE 78 9 1990 1481 1497
13. P.J. Rousseeuw, and A.M. Leroy Robust Regression and Outlier Detection 1986 Wiley & sons
14. G. Schwartz Estimating the dimension of a model Ann. of Statist 6 1979 461 464
15. M. Stone Cross-validatory choice and assessment of statistical predictions J. Roy. Statist. Soc. Ser B 36 1974 111 147
16. J.A.K. Suykens, J. De Brabanter, I. Lukas, and J. Vandewalle Weighted least squares support vector machines: robustness and sparse approximation Neurocomputing 48 1-4 2002 85 105
17. J.A.K. Suykens, T. Van Gestel, J. De Brabanter, B. De Moor, and J. Vandewalle Least Squares Support Vector Machines 2002 World Scientific Singapore
18. Y.N. Vapnik Statistical Learning Theory 1998 Wiley and Sons