The Theory and Applications of Generalized Logistic Regression for Risk Analysis of Fuzzy State(1)—A General Algorithm for Clustering Fuzzy Levels and Selecting Covariates

The concept and statistical methods for weakly correlative factors,influencing the formation and development of chronic diseases,are proposed in this paper.By the aid of fuzzy state analysis, the Cross-Product Difference Sum(CPDS)and the Akaike's Information Criterion(AIC),a general algorithm,clustering fuzzy exposure levels and selecting covariates,is designed for solving problems connected with analytical abilities of detecting and recognozing weakly correlative-influencing factors.