5 papers · 1 filter
Distance Profile Embedding for Independence and Conditional Independence Testing of Random Objects
Wenxi Tan, Bing Li, Lingzhou Xue
Testing independence or conditional independence is fundamental to statistical inference, yet existing methods for non-Euclidean random objects often face a difficult trade-off bet…
A Test for Treatment Heterogeneity under a Distributional Difference-in-Difference Framework
Satarupa Bhattacharjee, Bing Li, Lingzhou Xue
We develop a novel distributional Difference-in-Differences (DiD) framework to capture treatment heterogeneity across outcome distributions. By leveraging optimal transport, we use…
A Unified Framework for Nonlinear Mediation Analysis of Random Objects
Wenxi Tan, Bing Li, Lingzhou Xue
Mediation analysis for complex, non-Euclidean data, such as probability distributions, compositions, images, and networks, presents significant methodological challenges due to the…
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…
Nonlinear global Fréchet regression for random objects via weak conditional expectation
Satarupa Bhattacharjee, Bing Li, Lingzhou Xue
Random objects are complex non-Euclidean data taking value in general metric space, possibly devoid of any underlying vector space structure. Such data are getting increasingly abu…