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ergMargins  

Process Analysis for Exponential Random Graph Models
View on CRAN: Click here


Download and install ergMargins package within the R console
Install from CRAN:
install.packages("ergMargins")

Install from Github:
library("remotes")
install_github("cran/ergMargins")

Install by package version:
library("remotes")
install_version("ergMargins", "1.2")



Attach the package and use:
library("ergMargins")
Maintained by
Scott Duxbury
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2019-07-26
Latest Update: 2024-02-24
Description:
Calculates marginal effects and conducts process analysis in exponential family random graph models (ERGM). Includes functions to conduct mediation and moderation analyses and to diagnose multicollinearity. URL: . BugReports: . Duxbury, Scott W (2021) . Long, J. Scott, and Sarah Mustillo (2018) . Mize, Trenton D. (2019) . Karlson, Kristian Bernt, Anders Holm, and Richard Breen (2012) . Duxbury, Scott W (2018) . Duxbury, Scott W, Jenna Wertsching (2023) . Huang, Peng, Carter Butts (2023) .
How to cite:
Scott Duxbury (2019). ergMargins: Process Analysis for Exponential Random Graph Models. R package version 1.2, https://cran.r-project.org/web/packages/ergMargins
Previous versions and publish date:
0.1.0 (2019-07-26 13:00), 0.1.1 (2020-05-22 17:00), 0.1.2 (2021-02-23 15:50), 0.1.3.1 (2023-05-08 09:10), 0.1.3 (2021-06-30 09:40), 1.1 (2023-11-12 00:23), 1.2 (2024-02-24 06:00)
Other packages that cited ergMargins R package
View ergMargins citation profile
Other R packages that ergMargins depends, imports, suggests or enhances
Functions, R codes and Examples using the ergMargins R package
Some associated functions: edge.prob2 . ergm.mma . ergm.mod.mma . ergmAME . ergmMEM . vif.ergm . 
Some associated R codes: edgeprob2.R . ergm.mod.mma.R . ergmAME.R . ergmAME_boot.R . ergmAME_count.R . ergmCntPrep.R . ergmMEM.R . ergmMEM_boot.R . ergmMEM_count.R . ergmMMA.R . ergmMMA_boot.R . tergmprepare.R . timecov.R . vif.ergm.R .  Full ergMargins package functions and examples
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