Statistics and Its Interface
Volume 10 (2017)
Efficient feature screening for ultrahigh-dimensional varying coefficient models
Pages: 407 – 412
Feature screening in ultrahigh-dimensional varying coefficient 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 reallife 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.
ultrahigh-dimensionality, varying coefficient models, multiple index variables, group variables, conditional distance covariance
2010 Mathematics Subject Classification
62G08, 62G20, 62H20