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
Link To Document :
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