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IsingFit  

Fitting Ising Models Using the ELasso Method
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("IsingFit", "0.4")



Attach the package and use:
library("IsingFit")
Maintained by
Sacha Epskamp
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2014-02-17
Latest Update: 2023-10-03
Description:
This network estimation procedure eLasso, which is based on the Ising model, combines l1-regularized logistic regression with model selection based on the Extended Bayesian Information Criterion (EBIC). EBIC is a fit measure that identifies relevant relationships between variables. The resulting network consists of variables as nodes and relevant relationships as edges. Can deal with binary data.
How to cite:
Sacha Epskamp (2014). IsingFit: Fitting Ising Models Using the ELasso Method. R package version 0.4, https://cran.r-project.org/web/packages/IsingFit. Accessed 06 Mar. 2026.
Previous versions and publish date:
0.1.2 (2014-02-17 12:12), 0.2.0 (2014-04-23 12:28), 0.3.0 (2014-10-23 11:45), 0.3.1 (2016-09-07 13:01)
Other packages that cited IsingFit R package
View IsingFit citation profile
Other R packages that IsingFit depends, imports, suggests or enhances
Complete documentation for IsingFit
Functions, R codes and Examples using the IsingFit R package
Some associated functions: methods . 
Some associated R codes: ComparableNetworks.R . IsingFit.R . plot.IsingFit.R . print.IsingFit.R . summary.IsingFit.R .  Full IsingFit package functions and examples
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