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beam

This R package implements the method described in

Leday, G.G.R. and Richardson, S. (2019). Fast Bayesian inference in large Gaussian graphical models. Biometrics. 75(4), 1288--1298.

Description

Fast Bayesian inference of marginal and conditional independence structures from high-dimensional data.

Installation

If you wish to install beam from R:

# Install/load R package devtools
install.packages("devtools")
library(devtools)

# Install/load R package beam from github
install_github("gleday/beam")
library(beam)

Note that beam is maintained on github and only updated on CRAN every so often. Therefore, software versions may differ.

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Install

install.packages('beam')

Monthly Downloads

234

Version

2.0.4

License

GPL (>= 2.0)

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Maintainer

Gwenael G.R. Leday

Last Published

April 11th, 2025

Functions in beam (2.0.4)

beam-class

Class beam
beam.select

Edge selection with multiple testing and error control
TCPAprad

Protein expression data.
beam.select-class

Class beam.select
lightbeam

Fast inference of a conditional independence graph
beam

Bayesian inference in large Gaussian graphical models
beam-package

Fast Bayesian Inference in Large Gaussian Graphical Models