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math.ST2026
On the Impossibility of Specification Testing of Interference Models Based on Exposure Mappings
Chao Gao, Christopher Harshaw, Fredrik Sävje +1
Researchers use interference models based on exposure mappings to facilitate estimation of causal effects in randomized experiments with interference. To test the veracity of such…
math.ST2026
Adaptive Confidence Intervals in Efron's Gaussian Two-Groups Model
Qiaosen Wang, Shuwen Chai, Chao Gao
Robust uncertainty quantification is increasingly important in modern data analysis and is often formalized under Huber's model, which allows an -fraction of arbitrary…
math.ST2026
Confidence Intervals for Linear Models with Arbitrary Noise Contamination
Dong Xie, Chao Gao, John Lafferty
We study confidence interval construction for linear regression under Huber's contamination model, where an unknown fraction of noise variables is arbitrarily corrupted. While robu…