7 citations · 7 across the 9 of their papers we have counts for
10 papers
Generative modeling for the bootstrap
Leon Tran, Ting Ye, Peng Ding +1
Generative modeling builds on and substantially advances the classical idea of simulating synthetic data from observed samples. This paper shows that this principle is not only nat…
Decoupling and randomization for double-indexed permutation statistics
Mingxuan Zou, Jingfan Xu, Peng Ding +1
This paper introduces a version of decoupling and randomization to establish concentration inequalities for double-indexed permutation statistics. The results yield, among other ap…
Spectral analysis of large dimensional Chatterjee's rank correlation matrix
Zhaorui Dong, Fang Han, Jianfeng Yao
This paper studies the spectral behavior of large dimensional Chatterjee's rank correlation matrix when observations are independent draws from a high-dimensional random vector wit…
Bias correction for Chatterjee's graph-based correlation coefficient
Mona Azadkia, Leihao Chen, Fang Han
Azadkia and Chatterjee (2021) recently introduced a simple nearest neighbor (NN) graph-based correlation coefficient that consistently detects both independence and functional depe…
Structure of the with Hamiltonian Effective Field Theory
Fang-Chao Han, Zhan-Wei Liu, Derek B. Leinweber +1
We investigate the internal structure of the by analyzing lattice QCD simulation and experimental data within Hamiltonian effective field theory, considering both $J^P…
On a rank-based Azadkia-Chatterjee correlation coefficient
Leon Tran, Fang Han
Azadkia and Chatterjee (Azadkia and Chatterjee, 2021) recently introduced a graph-based correlation coefficient that has garnered significant attention. The method relies on a near…
Limit theorems of matching estimators with a fixed number of matches
Songliang Chen, Fang Han
This paper re-examines the limit theorems of Abadie and Imbens for nearest-neighbor matching estimators of average treatment effects with a fixed number of matches. We establish, f…
An Introduction to Permutation Processes (version 0.5)
Fang Han
These lecture notes were prepared for a special topics course in the Department of Statistics at the University of Washington, Seattle. They comprise the first eight chapters of a…
On the adaptation of causal forests to manifold data
Yiyi Huo, Yingying Fan, Fang Han
Researchers often hold the belief that random forests are "the cure to the world's ills" (Bickel, 2010). But how exactly do they achieve this? Focused on the recently introduced ca…
On propensity score matching with a diverging number of matches
Yihui He, Fang Han
This paper reexamines Abadie and Imbens (2016)'s work on propensity score matching for average treatment effect estimation. We explore the asymptotic behavior of these estimators w…