pggm: Profile Boosting for Gaussian Graphical Model

In pboost: Profile Boosting Framework for Parametric Models

Profile Boosting for Gaussian Graphical Model

Description

Profile boosting for Gaussian graphical model.

Usage

pggm(
  S,
  nObs,
  maxK = floor(min(nObs - 1, NROW(S) - 1, 50)),
  digits = 8,
  verbose = FALSE
)

Arguments

S	Covariance matrix.
nObs	Number of observations.
maxK	Maximum number of identified edges.
digits	Integer indicating the number of decimal places or significant digits to be used.
verbose	Print the procedure path?

Value

Index set of identified features.

Examples

library(MASS)
library(Matrix)

set.seed(2025)
n <- 1000
p <- 10

Omega <- Diagonal(p)
diag(Omega[1:4, 2:5]) <- diag(Omega[2:5, 1:4]) <- 0.5
Sigma <- chol2inv(chol(Omega))
X <- mvrnorm(n, rep(0, p), Sigma, empirical=TRUE)
S <- cov(X)
system.time( egg <- pggm(S, n) )

pboost documentation built on Jan. 9, 2026, 1:07 a.m.