lightbeam {beam} | R Documentation |
Fast inference of a conditional independence graph
Description
Fast and memory efficient reconstruction of large conditional independence networks.
Usage
lightbeam(X, thres = 0.1, method = "holm", verbose=TRUE)
Arguments
X |
n by p data matrix |
thres |
numeric. Significance threshold to be applied on adjusted tail probabilities. |
method |
character. Method to use for multiple comparison adjustment of tail probabilities. |
verbose |
logical. Whether information on progress should be be printed. |
Details
The function returns a sparse upper triangular matrix containing the (adjusted) tails probabilities that are below the given threshold (i.e. significant).
Value
An object of class dgCMatrix-class
Author(s)
Gwenael G.R. Leday
References
Leday, G.G.R. and Richardson, S. (2019). Fast Bayesian inference in large Gaussian graphical models. Biometrics.
Examples
# Load data
data(TCPAprad)
# beam
res <- lightbeam(X = TCPAprad, thres=0.1)
[Package beam version 2.0.4 Index]