Title
Feature screening for generalized varying coefficient models with application to dichotomous responses.
Abstract
Generalized varying coefficient model (GVCM) is an important extension of generalized linear model and varying coefficient model. It has been widely applied in many areas. This paper mainly considers the variable screening problem with dichotomous response data under GVCM, where a spline approximation is employed to estimate the coefficient function for each covariate. Two screening procedures based on marginal maximum likelihood estimation and marginal likelihood ratio statistics are studied. The sure independence screening property and the ranking consistency of these two approaches are established under some technical conditions. Some refined algorithms are presented to control the false selection rate. Extensive numerical studies are conducted to evaluate the performance of the proposed methodology.
Year
DOI
Venue
2016
10.1016/j.csda.2016.04.008
Computational Statistics & Data Analysis
Keywords
Field
DocType
Generalized varying coefficient model,Variable screening,High dimensional data,Sure screening property,Ranking consistency
Spline (mathematics),Econometrics,Clustering high-dimensional data,Covariate,Ranking,Maximum likelihood,Marginal likelihood,Generalized linear model,Statistics,Mathematics
Journal
Volume
Issue
ISSN
102
C
0167-9473
Citations 
PageRank 
References 
1
0.43
3
Authors
3
Name
Order
Citations
PageRank
Xiaochao Xia121.17
Hu Yang25017.12
Jialiang Li3578.21