| randnet.test {SemNeT} | R Documentation |
Test Against Random Networks
Description
Performs significance tests for global measures of semantic networks against the global measures of equivalent size (and density) random networks
Usage
randnet.test(..., iter, cores)
Arguments
... |
Matrices or data frames. Semantic networks to be compared against random networks |
iter |
Numeric.
Number of iterations in bootstrap.
Defaults to |
cores |
Number of computer processing cores to use for bootstrapping samples. Defaults to n - 1 total number of cores. Set to any number between 1 and maximum amount of cores on your computer |
Value
Returns a matrix containing p-values
for the network measures of the input networks against
the distribution of equivalent random networks. The last
two columns contain the mean ("M.rand") and
standard deviation ("SD.rand") of the network measures
for the random network distribution
Author(s)
Alexander Christensen <alexpaulchristensen@gmail.com>
References
Viger, F., & Latapy, M. (2016). Efficient and simple generation of random simple connected graphs with prescribed degree sequence. Journal of Complex Networks, 4, 15-37.
Examples
# Get openness data
one <- open.clean[which(open.group == "Low"),]
two <- open.clean[which(open.group == "High"),]
# Compute networks
net.one <- CN(one)
net.two <- CN(two)
# Perform random networks test
randnet.test(net.one, net.two, iter = 100, cores = 2)