Inclusion proportion graph
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).
bootInclude(bootobject, verbose = TRUE)
bootobject |
Nonparametric bootstrap results from |
verbose |
Logical, should progress be reported to the console? |
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 |
Sacha Epskamp <mail@sachaepskamp.com>
## 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)Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.