2 citations · 3 across the 6 of their papers we have counts for
4 papers · 1 filter
Conditional Mean Independence, Global Sensitivity Analysis, and Variable Screening Using nearest neighbor Graphs
Anirban Chatterjee, Ziang Niu, Bhaswar B. Bhattacharya
Quantifying how much of the variation in a response is explained by its conditional mean is central to many statistical problems. In this paper, we develop a unified framework for…
A Kernel-Based Conditional Two-Sample Test Using Nearest Neighbors (with Applications to Calibration, Regression Curves, and Simulation-Based Inference)
Anirban Chatterjee, Ziang Niu, Bhaswar B. Bhattacharya
In this paper we introduce a kernel-based measure for detecting differences between two conditional distributions. Using the `kernel trick' and nearest-neighbor graphs, we propose…
Reconciling model-X and doubly robust approaches to conditional independence testing
Ziang Niu, Abhinav Chakraborty, Oliver Dukes +1
Model-X approaches to testing conditional independence between a predictor and an outcome variable given a vector of covariates usually assume exact knowledge of the conditional di…
Estimation and inference for high-dimensional nonparametric additive instrumental-variables regression
Ziang Niu, Yuwen Gu, Wei Li
The method of instrumental variables provides a fundamental and practical tool for causal inference in many empirical studies where unmeasured confounding between the treatments an…