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研究生:鄭佳瑜
研究生(外文):Chia-Yu Cheng
論文名稱:用無母數迴歸法分析變數間之因果關係
論文名稱(外文):Determining the Cause-Effect Relationship between Two Variables by Nonparametric Regression
指導教授:洪志真洪志真引用關係洪慧念洪慧念引用關係
指導教授(外文):Dr.Jyh-Jen Horng ShiauDr.Hui-Nien Hung
學位類別:碩士
校院名稱:國立交通大學
系所名稱:統計所
學門:數學及統計學門
學類:統計學類
論文種類:學術論文
論文出版年:2003
畢業學年度:91
語文別:中文
論文頁數:39
中文關鍵詞:因果關係無母數迴歸
外文關鍵詞:Cause-EffectNonparametric Regressionparent-children relationship
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  • 被引用被引用:2
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在很多資料分析中,都有所謂的因果關係 (cause-effect relationship),也有另一種說法是親-子關係(parent-children relationship) ,例如身高與體重,身高增加一般可以讓體重自然地加重,但是加重體重卻無法達到長高的目的,這例子中身高就是因,體重則為果。若是基因間的關係,很多基因間都有活化(inspire/active)或抑制(depress/repress)的機制,A基因(parent)能活化B基因(child),並不代表B基因可以抑制或活化A基因。在不知道哪個變數才是親輩的情況下,如何衡量這樣的關係而且找出正確的親輩,一直就是現在科學家想探討的部分。而本文主要的目標是希望能從這樣有因果關係的資料主要是找出其方向性。
針對屬量的資料,之前的一些文獻使用貝氏網路 (Bayesian Network)方法去衡量變數之間的關係。本文則是提出一個使用無母數迴歸的方法來衡量資料的因果關係, 並討論其用於因果關係上的特性與限制
Consider the problem of determining the cause-effect relationship between two random variables X and Y from n pairs of independent and identically distributed data {(xi, yi), i=1,…,n}. Functional causal model with a causal graph is adopted to describe the causal relationship. The functional relationship is estimated by the smoothing spline estimation method.
Between the two causal graph candidates, “X→Y” and “Y→X”, we propose a selection criterion based on a Bayesian approach. A simulation study is conducted to evaluate the performance of the method. Results are promising. Some factors affecting the performance of the method are discussed.
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