1
Master of Science in Statistics, Shahrood University of Technology, Iran
2
Department of Statistics, Shahrood University of Technology, Iran
Abstract
In this paper, a new weighted fuzzy ridge regression method is proposed for a set of precise input data and triangular fuzzy output. For this purpose, the ridge estimator of the fuzzy parameters of the regression model is obtained and its predicted error is evaluated differently using a weighted fuzzy norm for precise ridge coefficients. To evaluate the proposed regression model, we introduce the generalized coefficient of determination. Then, by providing numerical examples, we compare the ordinary fuzzy regression model and the fuzzy ridge regression model using the mean square of the prediction errors and the fuzzy coefficient of determination. In the case of collinearity between the predictor variables, the results obtained from the fuzzy ridge regression model will be better than the results of the ordinary fuzzy regression.
Farokhi, M., Rabiei, M. & Arashi, M. (2017). Fuzzy two-parameter ridge regression analysis with exact input and triangular fuzzy output. Andishe_ye Amari, 21(2), 53-61.
MLA
Farokhi, M., Rabiei, M., & Arashi, M. "Fuzzy two-parameter ridge regression analysis with exact input and triangular fuzzy output", Andishe_ye Amari, 21, 2, 2017, 53-61.
HARVARD
Farokhi M., Rabiei M., Arashi M. (2017). 'Fuzzy two-parameter ridge regression analysis with exact input and triangular fuzzy output', Andishe_ye Amari, 21(2), pp. 53-61.
CHICAGO
M. Farokhi, M. Rabiei & M. Arashi, "Fuzzy two-parameter ridge regression analysis with exact input and triangular fuzzy output," Andishe_ye Amari, 21 2 (2017): 53-61,
VANCOUVER
Farokhi M., Rabiei M., Arashi M. Fuzzy two-parameter ridge regression analysis with exact input and triangular fuzzy output. Andishe_ye Amari. 2017;21(2):53-61 (In Persian).
