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研究生:鄭清仁
研究生(外文):Chin-Zen Cheng
論文名稱(外文):Influence Analysis of Nongaussianity by Applying Projection Pursuit
指導教授:黃郁芬黃郁芬引用關係
學位類別:碩士
校院名稱:國立中正大學
系所名稱:統計科學所
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:2006
畢業學年度:94
語文別:英文
論文頁數:41
外文關鍵詞:influence functionkurtosisnongaussianperturbationprojection pursuit.
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Gaussian distribution is the least structured from the
information-theoretic point of view. In this thesis, the projection
pursuit is performed by finding the most nongaussian projection to
explore the clustering structure of the data. We use kurtosis as a
measure of nongaussianity to find the projection direction. Kurtosis
is well known to be sensitive to abnormal observations, henceforth
the projection direction will be essentially affected by unusual
points. The perturbation theory provides a useful tool in
sensitivity analysis. In this thesis, we develop influence functions
for the projection direction to investigate the influence of unusual
observations. It is well-known that single-perturbation diagnostics
can suffer from the masking effect. Hence we also develop the
pair-perturbation influence functions to detect the masked
influential points and outliers. A simulated data and a specific
data example are provided to illustrate the applications of these
approaches.
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