README.md

In aefty/SQUIC_R: Sparse QUadratic approximate Inverse Covariance matrix estimation.

SQUIC R Interface Package

SQUIC is a second-order, L1-regularized maximum likelihood method for performant large-scale sparse precision matrix estimation. This repository contains the source code for the R interface of SQUIC.

Installation

Step 1:

Download the shared library libSQUIC from www.gitlab.ci.inf.usi.ch/SQUIC/libSQUIC, and follow its README instructions. The default and recommended location for libSQUIC is the home directory, i.e., ~/.

Step 2:

Run the following command to install the library:

library(devtools) 
install_github("www.gitlab.ci.inf.usi.ch/SQUIC/SQUIC_R")

Note: The devtools package can be install via the command install.packages("devtools").

Step 3:

Load the SQUIC package:

library(SQUIC)  

For further details type help(SQUIC) in the R command line.

Note: The number of threads used by SQUIC can be defined by setting the enviroment variable OMP_NUM_THREADS (e.g., base> export OMP_NUM_THREADS=12). This may require a restart of the session).

Example

To run a simple example :

library(SQUIC)

p = 1024
n = 100
lambda = .4

# generate a tridiagonal matrix
iC_star = Matrix::bandSparse(p, p, (-1):1, list(rep(-.5, p-1), rep(1.25,   p), rep(-.5, p-1)));

# generate the data
z    = replicate(n,rnorm(p));
iC_L = chol(iC_star);
data = matrix(solve(iC_L,z),p,n);

# Run SQUIC
out <- SQUIC(data,lambda)

aefty/SQUIC_R documentation built on July 29, 2021, 5:17 p.m.