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) <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.
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
RoxygenNote: 7.3.2
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2025-12-05 20:20:25 UTC; alex
Author: Alex Hayes [aut, cre, cph] (ORCID:
    <https://orcid.org/0000-0002-4985-5160>),
  Karl Rohe [aut, cph],
  Jun Tao [aut],
  Xintian Han [aut],
  Norbert Binkiewicz [aut]
Maintainer: Alex Hayes <alexpghayes@gmail.com>
Repository: CRAN
Date/Publication: 2025-12-06 15:20:02 UTC
Built: R 4.6.0; ; 2026-04-26 18:11:28 UTC; unix
