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fastRG

Sample Generalized Random Dot Product Graphs in Linear Time

v0.4.0 · Dec 6, 2025 · MIT + file LICENSE

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.

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r-devel-linux-x86_64-debian-gcc OK
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r-devel-windows-x86_64 OK
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Check History

OK 13 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE Jun 9, 2026
ERROR 12 OK · 0 NOTE · 0 WARNING · 1 ERROR · 0 FAILURE Jun 8, 2026
ERROR r-devel-linux-x86_64-debian-gcc

package dependencies

Package required but not available: ‘tidygraph’

See section ‘The DESCRIPTION file’ in the ‘Writing R Extensions’
manual.
OK 14 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE Mar 10, 2026

Reverse Dependencies (1)

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Dependency Network

Dependencies Reverse dependencies Matrix dplyr ggplot2 glue igraph rlang RSpectra tibble tidygraph tidyr gdim fastRG

Version History

6 tracked
new 0.4.0 Mar 10, 2026
updated 0.4.0 ← 0.3.3 diff Dec 5, 2025
updated 0.3.3 ← 0.3.2 diff Jul 23, 2025
updated 0.3.2 ← 0.3.1 diff Aug 20, 2023
updated 0.3.1 ← 0.3.0 diff Jun 29, 2022
new 0.3.0 Feb 25, 2021