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    Please use this identifier to cite or link to this item: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/74185


    Title: 多項式模型之共線性研究
    Other Titles: A study on the effect of multicollinearity in polynomial model
    Authors: 潘立翔;Pan, Li-Hsiang
    Contributors: 淡江大學數學學系碩士班
    王國徵;Wang, Kui-Jang
    Keywords: 多重共線性;Multicollinearity
    Date: 2011
    Issue Date: 2011-12-28 18:13:49 (UTC+8)
    Abstract: 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.
    Appears in Collections:[Graduate Institute & Department of Mathematics] Thesis

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