34 citations · 36 across the 7 of their papers we have counts for
7 papers
HSCI: Neyman-Orthogonal Causal Inference under High-Dimensional Proportional Hazards
Yingying Fan, Lan Gao, Daoji Li +1
Valid treatment effect inference in survival studies is fundamental yet challenging when the treatment assignments and outcomes are confounded by many baseline covariates. To this…
Knockoffs Inference under Privacy Constraints
Zhanrui Cai, Yingying Fan, Lan Gao
Model-X knockoff framework offers a model-free variable selection method that ensures finite sample false discovery rate (FDR) control. However, the complexity of generating knocko…
Asymptotic FDR Control with Model-X Knockoffs: Is Moments Matching Sufficient?
Yingying Fan, Lan Gao, Jinchi Lv +1
We propose a unified theoretical framework for studying the robustness of the model-X knockoffs framework by investigating the asymptotic false discovery rate (FDR) control of the…
ARK: Robust Knockoffs Inference with Coupling
Yingying Fan, Lan Gao, Jinchi Lv
We investigate the robustness of the model-X knockoffs framework with respect to the misspecified or estimated feature distribution. We achieve such a goal by theoretically studyin…
Refined Cramér Type Moderate Deviation Theorems for General Self-normalized Sums with Applications to Dependent Random Variables and Winsorized Mean
Lan Gao, Qi-Man Shao, Jiasheng Shi
Let {(X_i,Y_i)}_{i=1}^n be a sequence of independent bivariate random vectors. In this paper, we establish a refined Cramér type moderate deviation theorem for the general self-nor…
Asymptotic Distributions of High-Dimensional Distance Correlation Inference
Lan Gao, Yingying Fan, Jinchi Lv +1
Distance correlation has become an increasingly popular tool for detecting the nonlinear dependence between a pair of potentially high-dimensional random vectors. Most existing wor…
Optimal Nonparametric Inference with Two-Scale Distributional Nearest Neighbors
Emre Demirkaya, Yingying Fan, Lan Gao +3
The weighted nearest neighbors (WNN) estimator has been popularly used as a flexible and easy-to-implement nonparametric tool for mean regression estimation. The bagging technique…