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.

中文翻译：

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使用岭方法的直觉模糊部分逻辑回归模型

本文将岭估计方法应用于现有的具有精确预测因子、直觉模糊响应、直觉模糊系数和直觉模糊平滑函数的偏逻辑回归模型中，以改进存在多重共线性的现有直觉模糊偏逻辑回归模型。为此，岭方法也被用来估计参数直觉模糊系数和非参数直觉模糊平滑函数。一些常见的拟合优度标准也用于检查所提出的回归模型的性能。通过两个数值例子说明了所提出方法的潜在应用，并与直观的部分逻辑回归模型进行了比较。