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, .


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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.

Reference manual

It appears you don't have a PDF plugin for this browser. You can click here to download the reference manual.

install.packages("beam")

2.0.4 by Gwenael G.R. Leday, a year ago


https://github.com/gleday/beam


Browse source code at https://github.com/cran/beam


Authors: Gwenael G.R. Leday [cre, aut] , Ilaria Speranza [aut] , Harry Gray [ctb]


Documentation:   PDF Manual  


GPL (>= 2.0) license


Imports stats, methods, grDevices, graphics, Matrix, fdrtool, igraph, knitr, Rcpp, assertthat

Suggests covr, testthat

Linking to Rcpp, RcppArmadillo, BH


See at CRAN