DocumentCode :
1913317
Title :
Reinsch´s smoothing spline simulation metamodels
Author :
Santos, Pedro R. ; Santos, Isabel R.
Author_Institution :
Dept. of Comput. Sci. & Eng., Tech. Univ. of Lisbon (IST), Lisbon, Portugal
fYear :
2010
fDate :
5-8 Dec. 2010
Firstpage :
925
Lastpage :
934
Abstract :
Metamodels have been used frequently by the simulation community. However, not much research has been done with nonparametric metamodels compared with parametric metamodels. In this paper, smoothing splines for performing nonparametric metamodeling are presented. The use of smoothing splines on metamodeling fitting may provide functions that better approximate the behavior of the target simulation model, compared with linear and nonlinear regression metamodels. The smoothing splines tolerance parameter can be used to tune the smoothness of the resulting metamodel. A good experimental design is crucial for obtaining a better smoothing spline metamodel fitting, as illustrated in the examples.
Keywords :
mathematics computing; nonparametric statistics; regression analysis; splines (mathematics); tolerance analysis; linear regression metamodel; metamodeling fitting; nonlinear regression metamodel; nonparametric metamodel; parametric metamodel; reinsch smoothing spline simulation metamodel; simulation community; smoothing spline tolerance parameter; target simulation model; Data models; Least squares approximation; Mathematical model; Polynomials; Smoothing methods; Spline;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Simulation Conference (WSC), Proceedings of the 2010 Winter
Conference_Location :
Baltimore, MD
ISSN :
0891-7736
Print_ISBN :
978-1-4244-9866-6
Type :
conf
DOI :
10.1109/WSC.2010.5679097
Filename :
5679097
Link To Document :
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