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.

目錄
中文摘要
英文摘要
第一章 緒論
 第一節 研究動機…………………………………………………1
 第二節 研究目的…………………………………………………2                                      
 第三節 迴歸分析流程……………………………………………3
第二章 文獻探討
 第一節 多重共線性………………………………………………4
 第二節 變異數膨脹因子…………………………………………5
 第三節 程式簡介…………………………………………………5
第三章 研究資料及分析結果
 第一節 資料來源及介紹 ………………………………………17
 第二節 分析方法 ………………………………………………17
第四章 結論……………………………………………………………32
參考文獻（Reference）

表目錄
表一：%Model_Selection………………………………………………20
表二：%PAR_EST…………………………………………………………22
表三：%CORR_Selection………………………………………………22
表四：Model_Selection_CORR…………………………………………24
表五：%Test_Homo_Var_CORR_1………………………………………26
表六：%Test_Homo_Var_CORR_2………………………………………26
表七：%Test_Nomality_CORR…………………………………………27
表八：%Test_Homo_Var_CORR_1………………………………………28
表九：%Test_Homo_Var_CORR_2………………………………………28
表十：Model_Selection_CORR_CHK=YES………………………………29
表十一：Model_Selection_CORR_PRINCOMP_RIDGE_CHK=YES_1……31
表十二：Model_Selection_CORR_PRINCOMP_RIDGE _CHK=YES_2……31

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