ggm.generator: Simulate Data from Gaussian Graphical Model

In gif: Graphical Independence Filtering

Simulate Data from Gaussian Graphical Model

Description

Produce one or more samples from the specified Gaussian graphical model.

Usage

ggm.generator(n, Omega)

Arguments

n	The number of samples required.
Omega	The inverse covariance matrix of the specified Gaussian graphical model.

Value

A numeric matrix with n rows and p variables where p corresponds to the dimension of Omega.

Note

Omega should be positive definite.

Examples

library(gif)

set.seed(1)
n <- 200
p <- 100
Omega <- diag(1, p, p)
for(i in 1:(p - 1)) {
  Omega[i, i + 1] <- 0.5
  Omega[i + 1, i] <- 0.5
}
x <- ggm.generator(n, Omega)

gif documentation built on May 29, 2024, 1:12 a.m.