90 citations · 120 across the 4 of their papers we have counts for
6 papers
Dimension reduction for nonelliptically distributed predictors
Bing Li, Yuexiao Dong
Sufficient dimension reduction methods often require stringent conditions on the joint distribution of the predictor, or, when such conditions are not satisfied, rely on marginal t…
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…
Comment: Fisher Lecture: Dimension Reduction in Regression
Lexin Li, Christopher J. Nachtsheim
Comment: Fisher Lecture: Dimension Reduction in Regression [arXiv:0708.3774]
Comment: Fisher Lecture: Dimension Reduction in Regression
Bing Li
Comment: Fisher Lecture: Dimension Reduction in Regression [arXiv:0708.3774]
Determining the dimension of iterative Hessian transformation
R. Dennis Cook, Bing Li
The central mean subspace (CMS) and iterative Hessian transformation (IHT) have been introduced recently for dimension reduction when the conditional mean is of interest. Suppose t…
Contour regression: A general approach to dimension reduction
Bing Li, Hongyuan Zha, Francesca Chiaromonte
We propose a novel approach to sufficient dimension reduction in regression, based on estimating contour directions of small variation in the response. These directions span the or…