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Simulate Dynamic Networks using Exponential Random Graph Models (ERGM) Family

0packages depend
4.7Kdownloads / year
–test coverage
13/13flavors OK

Overview

About

Functions are provided to fit temporal lag models to dynamic networks. The models are build on top of exponential random graph models (ERGM) framework. There are functions for simulating or forecasting networks for future time points. Abhirup Mallik & Zack W. Almquist (2019) Stable Multiple Time Step Simulation/Prediction From Lagged Dynamic Network Regression Models, Journal of Computational and Graphical Statistics, 28:4, 967-979, <DOI: 10.1080/10618600.2019.1594834>.

Changes in 0.3.6

CRAN resubmission

  • Reformatted NEWS.md into a machine-readable package news file.
  • Fixed Rd markup in the package-level documentation.

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From NEWS.md in the release

Install

Health

CRAN checks
13OK
Slowest check: 4.6 min · r-oldrel-macos-x86_64
Status changes
  • OK13 OK2026-08-05
  • NOTE12 OK, 1 NOTE2026-08-01
  • OK13 OK2026-06-09
  • ERROR12 OK, 1 ERROR2026-06-08
  • OK14 OK2026-03-18
Show 1 earlier changeHide 1 earlier change
  • NOTE5 OK, 9 NOTE2026-03-10
Advisories

none known

Documentation

In release 0.3.6
READMEYes · 184 wordsVignettesYes · 1 · dynamicNEWSYes · 100% structured · mentions 0.3.6Citation fileNoWebsitenot declared in DESCRIPTION
Help pages
18 (1 internal)includes a package overview page
Examples that run
54%7 run in a plain check · 6 never run
Exported functions with examples
92%
Documented parameters
92%
Return-value docs
92%
Help pages citing references
0%

Downloads

4.7K
CRAN downloads in the past year
Rank #7,286 · ~13/day · ~394/mo
Daily download trend is not available in this view yet.
40730 days
1.2K90 days
4.7K1 year
Compare downloads with other packages →
Also on118 r2u2 autocran

Dependencies

Declared dependencies
8 external dependencies (excludes base and recommended)

Installing dnr adds 47 packages (28 with compiled code, 43 MB of source tarballs). Heaviest: stringi 11 MB, igraph 4.8 MB, lme4 4.1 MB.

Depends (3)
R >= 3.2.0networkergm
LinkingTo (0)
none
Suggests (2)
Enhances (0)
none
Reverse dependencies
0direct
0indirect

Nothing depends on this yet.

Datasets

People & History

People (2)
Author, Maintainer since 0.3.2 (2018)
Releases (4)

Pick two releases to compare their code metrics.

  • R
    R 4.6.0 released · 2026-04-24
  • 0.3.6Latest
    record
    2026-03-10 · current release · diff ↗
  • R
    R 4.5.0 released · 2025-04-11
  • R
    R 4.4.0 released · 2024-04-24
  • R
    R 4.3.0 released · 2023-04-21
  • R
    R 4.2.0 released · 2022-04-22
  • R
    R 4.1.0 released · 2021-05-18
  • 0.3.5
    record
    2020-11-30 · diff ↗ ·
    removed 1 export
    engineEdgeExperimental
  • R
    R 4.0.0 released · 2020-04-24
  • R
    R 3.6.0 released · 2019-04-26
  • 0.3.4
    record
    2018-07-26 · diff ↗ ·
    added 1 export
    engineEdgeExperimental
  • R
    R 3.5.0 released · 2018-04-23
  • 0.3.2
    record
    2018-02-23
  • R
    R 3.4.0 released · 2017-04-21

Package metadata

First published
2018-02-23
Total releases
4 / 8 yrs
License
GPL-3 OSI
Minimum R
≥ 3.2.0
Bundled data
1.3 MB / 2 files
Download size
1.1 MB
Appears in task views

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("dnr")
Mallik, A., & Almquist, Z. (2026). dnr: Simulate Dynamic Networks using Exponential Random Graph Models (ERGM) Family (Version 0.3.6) [Computer software]. https://doi.org/10.32614/CRAN.package.dnr

This package has no citation file, so citation() returns this entry built from DESCRIPTION.

Cite the R Observatory

For a number measured here: a download total, a coverage figure, an archival date.

APA

Balamuta, J. J. (2026). R Observatory: Metrics for dnr version 0.3.6 [Data set]. HJJB, LLC. Data release v2026-10-20. https://doi.org/10.5281/zenodo.21843040

From data release v2026-10-20, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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