Efficient feature screening for ultrahigh-dimensional varying coefficient models
Efficient feature screening for ultrahigh-dimensional varying coefficient models
复制标题
DOI：
10.4310/sii.2017.v10.n3.a5
复制
发表时间：
2017
影响因子：
0.8
通讯作者：
Xin Chen;Xuejun Ma;Xueqin Wang;Jingxiao Zhang
中科院分区：
文献类型：
--
作者：
Xin Chen;Xuejun Ma;Xueqin Wang;Jingxiao Zhang
Feature screening in ultrahigh-dimensional varying coef-ficient models is a crucial statistical problem in economics, genomics, etc. Current methods not only suffer from circumstances when the models involve multiple index variables or group predictor variables, but also cannot handle nonlinear varying coefficient models. To address these real-life scenarios efficiently, we develop a screening procedure for ultrahigh-dimensional varying coefficient models utilizing conditional distance covariance (CDC). Extensive simulation studies and two real economic data examples show the effectiveness and the flexibility of our proposed method.
