| نویسندگان | Mohammad Ghasem Akbari |
| نشریه | International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems |
| شماره صفحات | 527-543 |
| شماره سریال | 28 |
| شماره مجلد | 4 |
| ضریب تاثیر (IF) | 1 |
| نوع مقاله | Full Paper |
| تاریخ انتشار | 2020 |
| رتبه نشریه | ISI |
| نوع نشریه | چاپی |
| کشور محل چاپ | ایران |
| نمایه نشریه | JCR،Scopus |
| کلید واژه ها | Goodness, of, fit measureintuitionistic fuzzy numberintuitionistic fuzzy partial logistic regressionkernel methodridge estimation |
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چکیده مقاله
This paper applies a ridge estimation approach in an existing partial logistic regression model with exact predictors, intuitionistic fuzzy responses, intuitionistic fuzzy coefficients and intuitionistic fuzzy smooth function to improve an existing intuitionistic fuzzy partial logistic regression model in the presence of multicollinearity. For this purpose, ridge methodology is also involved to estimate the parametric intuitionistic fuzzy coefficients and nonparametric intuitionistic fuzzy smooth function. Some common goodness-of-fit criteria are also used to examine the performance of the proposed regression model. The potential application of the proposed method are illustrated and compared with the intuitionistic partial logistic regression model through two numerical examples. The results clearly indicate the proposed ridge method is quite efficient in model’s performances when there is multicollinearity among the predictors.