Leave-One-Out Neighborhood Smoothing for Graphons: Berry--Esseen Bounds and Edge-Wise Confidence Intervals
This work introduces a leave-one-out neighborhood smoother for graphon models to quantify uncertainty for every individual edge probability Pij. It achieves finite-sample concentration bounds and Berry–Esseen normal approximations for each pair, providing rigorous, entrywise confidence intervals based on local network structure.