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清華大學統計學研究所
國立清華大學統計學研究所
2017-03-17(五),主講人:呂恒輝 教授 (東海大學統計系)

清華大學、交通大學

統 計 學 研 究 所

專 題 演 講

 


講 題: An Inverse-regression Method of Dependent Variable Transformation for Dimension Reduction with Non-linear Confounding
演講者: 呂恒輝教授 (東海大學統計系)
時 間: 106年03月17日(星期五)10:40 - 12:00noon  (10:20 - 10:40am 茶會於統計所821室舉行)
地 點: 綜合三館837室
摘 要:

Many model-free dimension reduction methods have been developed for high-dimensional regression data but have not paid much attention on problems with non-linear confounding. In this paper, we propose an inverse-regression method of dependent variable transformation for detecting the presence of non-linear confounding. The benefit of using geometrical information from our method is highlighted. A ratio estimation strategy is incorporated in our approach to enhance the interpretation of variable selection. This approach can be implemented not only in principal Hessian directions (PHD) but also in other recently developed dimension reduction methods. Several simulation examples that are reported for illustration and comparisons are made with sliced inverse regression of Li (1997) and PHD in ignorance of non-linear confounding. An illustrative application to one real data is also presented.

 

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