From the 1 of 7 linked papers with an AI index.
7 papers
Gaussian Multiplier Bootstrap Procedure for the th Largest Coordinate of High-Dimensional Statistics
Yixi Ding, Qizhai Li, Yuke Shi +2
The paper develops Gaussian multiplier bootstrap techniques for estimating the distribution of the kth largest coordinate (or top‑k order statistics) in high‑dimensional settings,…
Limit theorems of Azadkia-Chatterjee's conditional graph correlation
Muhong Gao, Fang Han, Qizhai Li
Inferring the strength of conditional dependence and testing conditional independence are fundamental problems in statistics. A recent breakthrough by Azadkia and Chatterjee introd…
A Parameter-Centric View on Regression
Jingxin Yan, Lin Liu, Oliver Dukes +2
Discussion on ``Regression by Composition'' by Farewell, Daniel, Stensrud, and Huitfeldt
Principled Inference in Dense High-Dimensional Linear Models via Local Conditional Sparsity
Wenjun Xiong, Yan Chen, Mingya Long +1
High-dimensional inference methods often rely on coefficient sparsity, an assumption that can be restrictive when signals are dense but individually weak. In such settings, valid i…
Gaussian Approximations for the th coordinate of sums of random vectors
Yixi Ding, Qizhai Li, Yuke Shi +1
We consider the problem of Gaussian approximation for the th coordinate of a sum of high-dimensional random vectors. Such a problem has been studied previously for (i.e.…
Inverse regression for causal inference with multiple outcomes
Wei Zhang, Qizhai Li, Peng Ding
With multiple outcomes in empirical research, a common strategy is to define a composite outcome as a weighted average of the original outcomes. However, the choices of weights are…