bootnet (version 1.4.3)

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)

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

%% ~Describe the value returned %% If it is a LIST, use %% \item{comp1 }{Description of 'comp1'} %% \item{comp2 }{Description of 'comp2'} %% ...

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)
# }