sim.chordal: Simulate Chordal Network

In NetworkToolbox: Methods and Measures for Brain, Cognitive, and Psychometric Network Analysis

Description

Simulates a chordal network based on number of nodes. Data will also be simulated based on the true network structure

Usage

sim.chordal(
  nodes,
  inverse = c("cases", "matrix"),
  n = NULL,
  ordinal = FALSE,
  ordLevels = NULL,
  idio = NULL,
  eps = NULL
)

Arguments

nodes	Numeric. Number of nodes in the simulated network
inverse	Character. Method to produce inverse covariance matrix. "cases"Estimates inverse covariance matrix based on n number of cases and nodes number of variables, which are drawn from a random normal distribution rnorm. Data generated will be continuous unless ordinal is set to TRUE "matrix"Estimates inverse covariance matrix based on ??eps??
n	Numeric. Number of cases in the simulated dataset
ordinal	Boolean. Should simulated continuous data be converted to ordinal? Defaults to FALSE. Set to TRUE for simulated ordinal data
ordLevels	Numeric. If ordinal = TRUE, then how many levels should be used? Defaults to 5. Set to desired number of intervals
idio	Numeric. DESCRIPTION. Defaults to 0.10
eps	Numeric. DESCRIPTION. Defaults to 2

Value

Returns a list containing:

cliques	The cliques in the network
separators	The separators in the network
inverse	Simulated inverse covariance matrix of the network
data	Simulated data from sim.correlation in the psych package based on the simulated network

Author(s)

Guido Previde Massara <[e-mail]>

References

Massara, G. P. & Aste, T. (2019). Learning clique forests. ArXiv.

Examples

#Continuous data
sim.Norm <- sim.chordal(nodes = 20, inverse = "cases", n = 1000)

#Ordinal data
sim.Likert <- sim.chordal(nodes = 20, inverse = "cases", n = 1000, ordinal = TRUE)

#Dichotomous data
sim.Binary <- sim.chordal(nodes = 20, inverse = "cases", n = 1000, ordinal = TRUE, ordLevels = 5)

NetworkToolbox documentation built on May 28, 2021, 5:11 p.m.