ginettelafit/PCS: A partial correlation screening approach for controlling the false positive rate in sparse Gaussian Graphical Models

The R package includes functions to perform partical correlation screening to control the false positive rate better. The approach consists of two steps: First, it estimates an undirected network using one of the three state-of-the-art estimation approaches: nodewise regression using lasso, Glasso and SPACE. Second, it detects the false positives, by flagging the partial correlations that are smaller in absolute value than a given threshold, which is determined through cross-validation; the flagged correlations are set to zero.

install.packages("remotes")
remotes::install_github("ginettelafit/PCS")