4 papers
Structure-Preserving Nonlinear Sufficient Dimension Reduction for Tensors
Dianjun Lin, Bing Li, Lingzhou Xue
We introduce two nonlinear sufficient dimension reduction methods for regressions with tensor-valued predictors. Our goal is two-fold: the first is to preserve the tensor structure…
Collapsing Categories for Regression with Mixed Predictors
Chaegeun Song, Zhong Zheng, Bing Li +1
Categorical predictors are omnipresent in everyday regression practice: in fact, most regression data involve some categorical predictors, and this tendency is increasing in modern…
Variable Selection for Additive Global Fréchet Regression
Haoyi Yang, Satarupa Bhattacharjee, Lingzhou Xue +1
We present a novel framework for variable selection in Fréchet regression with responses in general metric spaces, a setting increasingly relevant for analyzing non-Euclidean data…
Doubly robust estimation of causal effects for random object outcomes with continuous treatments
Satarupa Bhattacharjee, Bing Li, Xiao Wu +1
Causal inference is central to statistics and scientific discovery, enabling researchers to identify cause-and-effect relationships beyond associations. While traditionally studied…