1 citations · 1 across the 3 of their papers we have counts for
3 papers
math.ST2026
Bootstrap consistency for general double/debiased machine learning estimators
Ziming Lin, Fang Han
Double/debiased machine learning (DML) provides a general framework for inference with high-dimensional or otherwise complex nuisance parameters by combining Neyman-orthogonal scor…
math.ST2024
On the consistency of bootstrap for matching estimators
Ziming Lin, Fang Han
In a landmark paper, Abadie and Imbens (2008) showed that the naive bootstrap is inconsistent when applied to nearest neighbor matching estimators of the average treatment effect w…
stat.ME2024★ 1 cited
Stabilized Inverse Probability Weighting via Isotonic Calibration
Lars van der Laan, Ziming Lin, Marco Carone +1
Inverse weighting with an estimated propensity score is widely used by estimation methods in causal inference to adjust for confounding bias. However, directly inverting propensity…