fastRG

Samples generalized random product graphs, a generalization of a broad class of network models. Given matrices X, S, and Y with with non-negative entries, samples a matrix with expectation XSY^T and independent Poisson or Bernoulli entries using the fastRG algorithm of Rohe et al. (2017) https://www.jmlr.org/papers/v19/17-128.html. The algorithm first samples the number of edges and then puts them down one-by-one. As a result it is O(m) where m is the number of edges, a dramatic improvement over element-wise algorithms that which require O(n^2) operations to sample a random graph, where n is the number of nodes.

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