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Martingale Difference Correlation and High Dimensional Feature Screening

作者: 发布时间:2014-06-30 点击数:
主讲人:邵晓峰 副教授(伊利诺大学香槟分校)
主讲人简介: 伊利诺大学香槟分校统计系副教授
 
主持人:
讲座简介: In this talk, I will introduce a new metric, the so-called martingale difference correlation to measure the conditional mean dependence between a scalar response variable V and a vector predictor variable U. Our metric is a natural extension of the recently proposed distance correlation, which is used to measure the dependence between V and U. The martingale difference correlation and its empirical counterpart inherit a number of desirable features of distance correlation and sample distance correlation, such as algebraic simplicity and elegant theoretical properties. We further use martingale difference correlation as a marginal utility to do high dimensional feature screening to screen out variables that do not contribute to conditional mean of the response given the covariates. An extension to conditional quantile screening will be described and sure screening consistency for both screening procedures will also be presented. I will conclude the talk by showing selected simulation results and a real data illustration, which demonstrate the effectiveness of martingale difference correlation based screening procedures in comparison with the existing counterparts.
时间:2014年6月30日(周一)下午16:30-18:00
地点:经济楼N303室
讲座语言:English
主办单位:王亚南经济研究院、永利集团3044官网欢迎您
承办单位:王亚南经济研究院
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