66 citations · 112 across the 6 of their papers we have counts for
6 papers
High-dimensional Variable Screening via Conditional Martingale Difference Divergence
Lei Fang, Qingcong Yuan, Xiangrong Yin +1
Variable screening has been a useful research area that deals with ultrahigh-dimensional data. When there exist both marginally and jointly dependent predictors to the response, ex…
Weighted Orthogonal Components Regression Analysis
Xiaogang Su, Yaa Wonkye, Pei Wang +1
In the multiple linear regression setting, we propose a general framework, termed weighted orthogonal components regression (WOCR), which encompasses many known methods as special…
On efficient dimension reduction with respect to a statistical functional of interest
Wei Luo, Bing Li, Xiangrong Yin
We introduce a new sufficient dimension reduction framework that targets a statistical functional of interest, and propose an efficient estimator for the semiparametric estimation…
Sufficient dimension reduction based on an ensemble of minimum average variance estimators
Xiangrong Yin, Bing Li
We introduce a class of dimension reduction estimators based on an ensemble of the minimum average variance estimates of functions that characterize the central subspace, such as t…
A Note on Sliced Inverse Regression with Regularizations
Caroline Bernard-Michel, Laurent Gardes, Stéphane Girard
In "Li, L. and Yin, X. (2008). Sliced Inverse Regression with Regularizations. Biometrics, 64(1):124--131" a ridge SIR estimator is introduced as the solution of a minimization pro…
On surrogate dimension reduction for measurement error regression: An invariance law
Bing Li, Xiangrong Yin
We consider a general nonlinear regression problem where the predictors contain measurement error. It has been recently discovered that several well-known dimension reduction metho…