Leave-One-Out Neighborhood Smoothing for Graphons: Berry--Esseen Bounds and Edge-Wise Confidence Intervals

We develop a framework for edge-wise inference in graphon-based random networks. The proposed leave-one-out neighborhood procedure excludes the target vertex when selecting neighbors, then averages the selected vertices' edges to that target. Conditional on the latent probabilities and selected neig