Random Graph Sampling

Random graph sampling supports claims about estimating full SND because omitted edges are treated as missing samples rather than excluded relationships. The Horvitz-Thompson estimator for Bernoulli sampling is unbiased for SND. Bernoulli-p random graphs include each unordered agent pair independently with probability p. The Horvitz-Thompson estimator uses 1/p weights and population normalization so it remains unbiased even with an empty sampled edge set. The normalized Graph-SND statistic is a uniform sample mean conditional on at least one sampled edge.