237 citations · 883 across the 24 of their papers we have counts for
13 papers · 1 filter
A nonparametric test for elliptical distribution based on kernel embedding of probabilities
Yin Tang, Bing Li
Elliptical distribution is a basic assumption underlying many multivariate statistical methods. For example, in sufficient dimension reduction and statistical graphical models, thi…
Independent component analysis for multivariate functional data
Joni Virta, Bing Li, Klaus Nordhausen +1
We extend two methods of independent component analysis, fourth order blind identification and joint approximate diagonalization of eigen-matrices, to vector-valued functional data…
JADE for Tensor-Valued Observations
Joni Virta, Bing Li, Klaus Nordhausen +1
Independent component analysis is a standard tool in modern data analysis and numerous different techniques for applying it exist. The standard methods however quickly lose their e…
Independent component analysis for tensor-valued data
Joni Virta, Bing Li, Klaus Nordhausen +1
In preprocessing tensor-valued data, e.g. images and videos, a common procedure is to vectorize the observations and subject the resulting vectors to one of the many methods used f…
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…
A general theory for nonlinear sufficient dimension reduction: Formulation and estimation
Kuang-Yao Lee, Bing Li, Francesca Chiaromonte
In this paper we introduce a general theory for nonlinear sufficient dimension reduction, and explore its ramifications and scope. This theory subsumes recent work employing reprod…