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DESCRIPTION
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Package: fastRG
Title: Sample Generalized Random Dot Product Graphs in Linear Time
Version: 0.3.2.9000
Authors@R: c(
person("Alex", "Hayes", , "[email protected]", role = c("aut", "cre", "cph"),
comment = c(ORCID = "0000-0002-4985-5160")),
person("Karl", "Rohe", , "[email protected]", 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,
knitr,
magrittr,
rmarkdown,
testthat (>= 3.0.0)
Config/testthat/edition: 3
Encoding: UTF-8
Roxygen: list(markdown = TRUE)
RoxygenNote: 7.3.2