文献详情
Model-free conditional feature screening with exposure variables
文献类型：期刊
通讯作者：Liu, JY (reprint author), Xiamen Univ, Dept Stat, Sch Econ, Wang Yanan Inst Studies Econ,Fujian Key Lab Stat, Xiamen, Peoples R China.
期刊名称：STATISTICS AND ITS INTERFACE影响因子和分区
年：2019
卷：12
期：2
页码：239-251
ISSN：1938-7989
关键词：Conditional screening; Feature screening; Exposure variable; Model-free; Sure screening property; Variable selection
所属部门：统计与大数据研究院
摘要：In high dimensional analysis, effects of explanatory variables on responses sometimes rely on certain exposure variables, such as time or environmental factors. In this paper, to characterize the importance of each predictor, we utilize its conditional correlation given exposure variables with the empirical distribution function of response. A model-free conditional screening method is subsequently advocated based on this idea, aiming to identify significant predictors whose effects may vary wit ...More
In high dimensional analysis, effects of explanatory variables on responses sometimes rely on certain exposure variables, such as time or environmental factors. In this paper, to characterize the importance of each predictor, we utilize its conditional correlation given exposure variables with the empirical distribution function of response. A model-free conditional screening method is subsequently advocated based on this idea, aiming to identify significant predictors whose effects may vary with the exposure variables. The proposed screening procedure is applicable to any model form, including that with heteroscedasticity where the variance component may also vary with exposure variables. It is also robust to extreme values or outlier. Under some mild conditions, we establish the desirable sure screening and the ranking consistency properties of the screening method. The finite sample performances are illustrated by simulation studies and an application to the breast cancer dataset. ...Hide

百度学术：Model-free conditional feature screening with exposure variables
语言：外文
基金：National Natural Science Foundation of China (NSFC)National Natural Science Foundation of China [11771361, JAS14007, 11371236, 11422107]; Fundamental Research Funds for the Scientific Research Foundation for the Returned Overseas Chinese Scholars; Henry Fok Education Foundation Fund of Young College Teachers [141002]
作者其他论文



MODEL-FREE FEATURE SCREENING FOR ULTRAHIGH DIMENSIONAL DATATHROUGH A MODIFIED BLUM-KIEFER-ROSENBLATT CORRELATION.Zhou, Yeqing, Zhu, Liping,.STATISTICA SINICA. 2018, 28(3), 1351-1370.
Test for conditional independence with application to conditional screening.Zhou, Yeqing, Liu, Jingyuan, Zhu, Liping,.JOURNAL OF MULTIVARIATE ANALYSIS. 2020, 175.
Test for conditional independence with application to conditional screening.Zhou, Yeqing, Liu, Jingyuan, Zhu, Liping,.JOURNAL OF MULTIVARIATE ANALYSIS. 2020, 175.