fastRG: Sample Generalized Random Dot Product Graphs in Linear Time

Samples generalized random product graph, 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 X S Y^T and independent Poisson or Bernoulli entries using the fastRG algorithm of Rohe et al. (2017) <>. 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.

Getting started

Package details

AuthorAlex Hayes [aut, cre, cph] (<>), Karl Rohe [aut, cph], Jun Tao [aut], Xintian Han [aut], Norbert Binkiewicz [aut]
MaintainerAlex Hayes <>
LicenseMIT + file LICENSE
Package repositoryView on CRAN
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fastRG documentation built on June 30, 2022, 9:06 a.m.