bootInclude: Inclusion proportion graph

Description

This function takes bootstrap results and returns a inclusion probability network (edge weights indicate how often a certain edge was included in the model). Note that the plotting method automatically uses a black-white color scheme (as edges are not signed and always positive).

Usage

bootInclude(bootobject, verbose = TRUE)

Value

A bootnetResult object with the following elements:

graph: The weights matrix of the network
intercepts: The intercepts
results: The results of the estimation procedure
labels: A vector with node labels
nNode: Number of nodes in the network
nPerson: Number of persons in the network
input: Input used, including the result of the default set used

Arguments

bootobject: Nonparametric bootstrap results from bootnet
verbose: Logical, should progress be reported to the console?

Author

Sacha Epskamp <mail@sachaepskamp.com>

Examples

Run this code

if (FALSE) {
# BFI Extraversion data from psychTools package:
library("psychTools")
data(bfi)
# Subset of data:
bfiSub <- bfi[1:250,1:25]

# Estimate ggmModSelect networks (not stepwise to increase speed):
Network <- estimateNetwork(bfiSub, default = "ggmModSelect", corMethod = "cor",
              stepwise = FALSE)

# Bootstrap 100 values, using 8 cores (100 to incease speed, preferably 1000+):
boots <- bootnet(Network, nBoots = 100, nCores = 8)

# Threshold network:
Network_inclusion <- bootInclude(boots)

# Plot:
plot(Network_inclusion)
}