• 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