COMPARATIVE ANALYSIS FOR FUZZY NONPARAMETRIC REGRESSION MODELS

Münevvere Yıldız; Memmedağa Memmedli

doi:10.18038/estubtda.1033350

TR EN

COMPARATIVE ANALYSIS FOR FUZZY NONPARAMETRIC REGRESSION MODELS

Abstract

Statistical modeling is essential to revealing the relationships between variables. These statistical models can be classified as parametric and nonparametric methods in studies using crisp values. However, most of the collected data are inherently fuzzy. In this context, the fuzzy expression of methods using precise data is a matter of curiosity for researchers. The methods with fuzzy input and output variables have been developed for a long time. The study aims to describe nonparametric local polynomial regression models in fuzzy structure to examine the results for cases where the input variable is a crisp number, and the output variable is a symmetrical triangular and trapezoidal fuzzy number. According to the results, the bandwidth parameter was smaller in models where the degree of the polynomial was taken as one and larger in the case of three. In addition, the bandwidth parameter was found to be larger in models using the Epanechnikov kernel.

Keywords

Fuzzy local polynomial regression, Symmetric triangular fuzzy number, Trapezoidal fuzzy number, Generalized cross-validation, Mean square error

COMPARATIVE ANALYSIS FOR FUZZY NONPARAMETRIC REGRESSION MODELS

Abstract

Statistical modeling is essential in revealing the relationships between variables. These models can be classified as parametric and nonparametric methods in studies using crisp values. However, most of the data collected are inherently fuzzy. In this framework, it has been a subject that has been studied from past to present that the methods derived for exact values are expressed as methods with fuzzy valued input and output variables. The study aims to describe nonparametric local polynomial regression models in fuzzy structure to examine the results for cases where an input variable is a crisp number, and the output variable is a symmetrical triangular and trapezoidal fuzzy number. According to the results, the bandwidth parameter was smaller in models where the degree of the polynomial was taken as one and larger in the case of three. In addition, the bandwidth parameter was found to be larger in models using the Epanechnikov kernel.

Keywords

fuzzy local polynomial regression, symmetric triangular fuzzy number, trapezoidal fuzzy number, generalized cross-validation, Mean square error

References

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Details

Primary Language

English

Subjects

-

Journal Section

Research Article

Authors

Münevvere Yıldız ^*
0000-0001-9541-2603
Türkiye

Memmedağa Memmedli
0000-0002-9967-4237
Türkiye

Publication Date

December 29, 2021

Submission Date

December 6, 2021

Acceptance Date

December 22, 2021

Published in Issue

Year 2021 Volume: 22 Number: 4

DOI

https://doi.org/10.18038/estubtda.1033350

IZ

https://izlik.org/JA46ET65FA

APA

Yıldız, M., & Memmedli, M. (2021). COMPARATIVE ANALYSIS FOR FUZZY NONPARAMETRIC REGRESSION MODELS. Eskişehir Technical University Journal of Science and Technology A - Applied Sciences and Engineering, 22(4), 353-365. https://doi.org/10.18038/estubtda.1033350

AMA

1.Yıldız M, Memmedli M. COMPARATIVE ANALYSIS FOR FUZZY NONPARAMETRIC REGRESSION MODELS. Estuscience - Se. 2021;22(4):353-365. doi:10.18038/estubtda.1033350

Chicago

Yıldız, Münevvere, and Memmedağa Memmedli. 2021. “COMPARATIVE ANALYSIS FOR FUZZY NONPARAMETRIC REGRESSION MODELS”. Eskişehir Technical University Journal of Science and Technology A - Applied Sciences and Engineering 22 (4): 353-65. https://doi.org/10.18038/estubtda.1033350.

EndNote

Yıldız M, Memmedli M (December 1, 2021) COMPARATIVE ANALYSIS FOR FUZZY NONPARAMETRIC REGRESSION MODELS. Eskişehir Technical University Journal of Science and Technology A - Applied Sciences and Engineering 22 4 353–365.

IEEE

[1]M. Yıldız and M. Memmedli, “COMPARATIVE ANALYSIS FOR FUZZY NONPARAMETRIC REGRESSION MODELS”, Estuscience - Se, vol. 22, no. 4, pp. 353–365, Dec. 2021, doi: 10.18038/estubtda.1033350.

ISNAD

Yıldız, Münevvere - Memmedli, Memmedağa. “COMPARATIVE ANALYSIS FOR FUZZY NONPARAMETRIC REGRESSION MODELS”. Eskişehir Technical University Journal of Science and Technology A - Applied Sciences and Engineering 22/4 (December 1, 2021): 353-365. https://doi.org/10.18038/estubtda.1033350.

JAMA

1.Yıldız M, Memmedli M. COMPARATIVE ANALYSIS FOR FUZZY NONPARAMETRIC REGRESSION MODELS. Estuscience - Se. 2021;22:353–365.

MLA

Yıldız, Münevvere, and Memmedağa Memmedli. “COMPARATIVE ANALYSIS FOR FUZZY NONPARAMETRIC REGRESSION MODELS”. Eskişehir Technical University Journal of Science and Technology A - Applied Sciences and Engineering, vol. 22, no. 4, Dec. 2021, pp. 353-65, doi:10.18038/estubtda.1033350.

Vancouver

1.Münevvere Yıldız, Memmedağa Memmedli. COMPARATIVE ANALYSIS FOR FUZZY NONPARAMETRIC REGRESSION MODELS. Estuscience - Se. 2021 Dec. 1;22(4):353-65. doi:10.18038/estubtda.1033350

COMPARATIVE ANALYSIS FOR FUZZY NONPARAMETRIC REGRESSION MODELS

Abstract

Keywords

COMPARATIVE ANALYSIS FOR FUZZY NONPARAMETRIC REGRESSION MODELS

Abstract

Keywords

References

Details

Primary Language

Subjects

Journal Section

Authors

Publication Date

Submission Date

Acceptance Date

Published in Issue

DOI

IZ

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