Package: fastRG Title: Sample Generalized Random Dot Product Graphs in Linear Time Version: 0.4.0 Authors@R: c( person("Alex", "Hayes", , "alexpghayes@gmail.com", role = c("aut", "cre", "cph"), comment = c(ORCID = "0000-0002-4985-5160")), person("Karl", "Rohe", , "KarlRohe@stat.wisc.edu", role = c("aut", "cph")), person("Jun", "Tao", role = "aut"), person("Xintian", "Han", role = "aut"), person("Norbert", "Binkiewicz", role = "aut") ) Description: 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 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. License: MIT + file LICENSE URL: https://rohelab.github.io/fastRG/, https://github.com/RoheLab/fastRG BugReports: https://github.com/RoheLab/fastRG/issues Depends: Matrix Imports: dplyr, ggplot2, glue, igraph, methods, rlang (>= 1.0.0), RSpectra, stats, tibble, tidygraph, tidyr Suggests: covr, irlba, knitr, magrittr, purrr, rmarkdown, scales, testthat (>= 3.0.0) Config/testthat/edition: 3 Encoding: UTF-8 Roxygen: list(markdown = TRUE) RoxygenNote: 7.3.2 VignetteBuilder: knitr Config/pak/sysreqs: libglpk-dev libicu-dev libxml2-dev Repository: https://rohelab.r-universe.dev Date/Publication: 2025-12-05 20:49:42 UTC RemoteUrl: https://github.com/rohelab/fastrg RemoteRef: HEAD RemoteSha: 01579e164cee36cd58aed71d760bda08726beb91 NeedsCompilation: no Packaged: 2026-06-09 07:29:46 UTC; root Author: Alex Hayes [aut, cre, cph] (ORCID: ), Karl Rohe [aut, cph], Jun Tao [aut], Xintian Han [aut], Norbert Binkiewicz [aut] Maintainer: Alex Hayes