beam: Fast Bayesian Inference in Large Gaussian Graphical Models

Fast Bayesian inference of marginal and conditional independence structures from high-dimensional data. Leday and Richardson (2019), Biometrics, <doi:10.1111/biom.13064>.

Version:	2.0.2
Depends:	R (≥ 3.1.0)
Imports:	stats, methods, grDevices, graphics, Matrix, fdrtool, igraph, knitr, Rcpp, assertthat
LinkingTo:	Rcpp, RcppArmadillo, BH
Suggests:	covr, testthat
Published:	2020-05-28
Author:	Gwenael G.R. Leday [cre, aut], Ilaria Speranza [aut], Harry Gray [ctb]
Maintainer:	Gwenael G.R. Leday <gwenael.leday at wur.nl>
License:	GPL-2 | GPL-3 [expanded from: GPL (≥ 2.0)]
URL:	https://github.com/gleday/beam
NeedsCompilation:	yes
Materials:	README NEWS
CRAN checks:	beam results

Documentation:

Reference manual:

beam.pdf

Downloads:

Package source:	beam_2.0.2.tar.gz
Windows binaries:	r-devel: beam_2.0.2.zip, r-release: beam_2.0.2.zip, r-oldrel: beam_2.0.2.zip
macOS binaries:	r-release (arm64): beam_2.0.2.tgz, r-oldrel (arm64): beam_2.0.2.tgz, r-release (x86_64): beam_2.0.2.tgz, r-oldrel (x86_64): beam_2.0.2.tgz
Old sources:	beam archive

Linking:

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