本論文在研究迴歸分析的過程中容易產生出共線性的問題,而在以往的資料中大部分共線性問題都是以;(1)將彼此相關係數較高的預測變項只取一個重要變項投入分析,(2)脊迴歸(ridge regression),(3)主成分迴歸(principle regression)這三種方法來去解決共線性問題,但因其中都有一些不適的地方,所以此篇論文目的在探討一個新的方法去解決共線性問題,並與脊迴歸與主成分迴歸去做比較。 In this paper the process of regression analysis of linear prone to the problem, and most of the information in the past, collinearity problems are to; (1) the high correlation coefficient with each other predictors just take a important variable into analysis, (2) ridge regression, (3) principal component regression a total of three methods to solve linear problems come and go, but some of them are not local, so paper Cipian aims to investigate a new method to solve the collinearity problem, and with the ridge regression and principal component regression to do more.