beam (version 2.0.4)

lightbeam: 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)

Value

An object of class dgCMatrix-class

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.

Author

Gwenael G.R. Leday

Details

The function returns a sparse upper triangular matrix containing the (adjusted) tails probabilities that are below the given threshold (i.e. significant).

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)