bootInclude: Inclusion proportion graph

In bootnet: Bootstrap Methods for Various Network Estimation Routines

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)

Arguments

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

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
nNodes	Number of nodes in the network
nPerson	Number of persons in the network
input	Input used, including the result of the default set used

Author(s)

Sacha Epskamp <[e-mail]>

See Also

bootnet, estimateNetwork

Examples

## Not run: 
# 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)

## End(Not run)

bootnet documentation built on May 29, 2024, 8:38 a.m.