2 citations · 2 across the 4 of their papers we have counts for
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Quantitative CLTs for Geometric Statistics of Dependent Marked Point Processes
Tianshu Cong, Aihua Xia, J. E. Yukich
Given a geometric statistic expressible as a sum of scores which depend on local data, \citet{BYY19} established central limit theorems for centered and normalized versions of thes…
Convergence rate for geometric statistics of point processes with fast decay dependence
Tianshu Cong, Aihua Xia
[Błaszczyszyn, Yogeshwaran and Yukich (2019)] established central limit theorems for geometric statistics of point processes having fast decay dependence. As limit theorems are of…
Normal approximation in total variation for statistics in geometric probability
Tianshu Cong, Aihua Xia
We use Stein's method to establish the rates of normal approximation in terms of the total variation distance for a large class of sums of score functions of marked Poisson point p…
A large sample property in approximating the superposition of i.i.d. point processes
Tianshu Cong, Aihua Xia, Fuxi Zhang
One of the main differences between the central limit theorem and the Poisson law of small numbers is that the former possesses the large sample property (LSP), i.e., the error of…