Ridge-type pretest and shrinkage estimations in partially linear models

Analysis of Potential Factors Influencing China’s Regional Sustainable Economic Growth

The purpose of this article is to screen out the most important factors affecting China’s economic growth. Based on a literature review and relevant financial theoretical knowledge, China’s economic growth factors are selected from international and domestic aspects. Four methods, including least squares estimation, stepwise regression, ridge regression estimation, and Lasso regression, are used to screen and optimize 12 variables and analyze the degrees of influence empirically. The study finds that consumption levels and the development of the tertiary industry play significant roles in promoting China’s economic growth. Additionally, financial development and industrialization promote China’s economic growth, although in a gradual manner.

Intuitionistic Fuzzy Partial Logistic Regression Model Using Ridge Methodology

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.