• DocumentCode
    1677583
  • Title

    Comparison study on smoothing parameter and sample size in nonparametric fuzzy local polynomial regression models

  • Author

    Memmedli, M. ; Yildiz, Metin

  • Author_Institution
    Anadolu Univ., Eskisehir, Turkey
  • fYear
    2012
  • Firstpage
    1
  • Lastpage
    3
  • Abstract
    In this paper, we considered the relationship between the smoothing parameter value and sample size as a simulation study in nonparametric fuzzy local polynomial regression. For this aim, we developed fuzzy version of generalized cross-validation criteria (GCV) for selecting smoothing parameter in nonparametric fuzzy local polynomial models. Besides the local linear models, local cubic models are also used in these simulations. The appropriate smoothing parameters are selected by GCV criteria for different sample size and then performances of the models are compared using these appropriate smoothing parameters with sample sizes.
  • Keywords
    fuzzy set theory; nonparametric statistics; polynomials; regression analysis; sampling methods; smoothing methods; GCV criteria; generalized cross-validation criteria; local cubic models; local linear models; nonparametric fuzzy local polynomial regression models; sample size; smoothing parameter value; Local polynomial smoothing; fuzzy nonparametric regression; generalized cross validation; sample size;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Problems of Cybernetics and Informatics (PCI), 2012 IV International Conference
  • Conference_Location
    Baku
  • Print_ISBN
    978-1-4673-4500-2
  • Type

    conf

  • DOI
    10.1109/ICPCI.2012.6486400
  • Filename
    6486400