rIsing: High-Dimensional Ising Model Selection

Fits an Ising model to a binary dataset using L1 regularized logistic regression and extended BIC. Also includes a fast lasso logistic regression function for high-dimensional problems. Uses the 'libLBFGS' optimization library by Naoaki Okazaki.

Version: 0.1.0
Depends: R (≥ 3.1.0)
Imports: Rcpp (≥ 0.12.8), data.table (≥ 1.9.6)
LinkingTo: Rcpp, RcppEigen (≥
Suggests: igraph, IsingSampler
Published: 2016-11-25
DOI: 10.32614/CRAN.package.rIsing
Author: Pratik Ramprasad [aut, cre], Jorge Nocedal [ctb, cph], Naoaki Okazaki [ctb, cph]
Maintainer: Pratik Ramprasad <pratik.ramprasad at gmail.com>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: yes
CRAN checks: rIsing results


Reference manual: rIsing.pdf


Package source: rIsing_0.1.0.tar.gz
Windows binaries: r-devel: rIsing_0.1.0.zip, r-release: rIsing_0.1.0.zip, r-oldrel: rIsing_0.1.0.zip
macOS binaries: r-release (arm64): rIsing_0.1.0.tgz, r-oldrel (arm64): rIsing_0.1.0.tgz, r-release (x86_64): rIsing_0.1.0.tgz, r-oldrel (x86_64): rIsing_0.1.0.tgz


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