3 papers
stat.ME2026
Integrating Heterogeneous Information in Randomized Experiments: A Unified Calibration Framework
Wei Ma, Zeqi Wu, Zheng Zhang
In modern randomized experiments, large-scale data collection increasingly yields rich baseline covariates and auxiliary information from multiple sources. Such information offers…
econ.EM2025
Limit Theorems for Network Data without Metric Structure
Wen Jiang, Yachen Wang, Zeqi Wu +1
This paper develops limit theorems for random variables with network dependence, without requiring the individuals in the network to be located in a Euclidean or metric space. This…
stat.ME2025
A New and Efficient Debiased Estimation of General Treatment Models by Balanced Neural Networks Weighting
Zeqi Wu, Meilin Wang, Wei Huang +1
Estimation and inference of treatment effects under unconfounded treatment assignments often suffer from bias and the `curse of dimensionality' due to the nonparametric estimation…