removing_and_randomizing: calculates how much of a network's perceived structure is due...

In hemprichbennett/netReducer: Analysing the impact of sample size and species composition in network analysis

Description

This function removes each species in turn, randomizing the resulting matrix and returning the desired metric value for the resulting random subnetworks

Usage

removing_and_randomizing(network, index, network_level = "higher",
  sums_to_preserve = "both", datatype = "list", nreplicates = 1000)

Arguments

network	Your input object
index	The network-level metric, from bipartite, which you desire to be calculated
network_level	The network level to be removing and randomizing. Currently only 'higher' works
sums_to_preserve	preserve sums of columns, rows, or both
datatype	is it a matrix of interactions, or a list of matrixes?
nreplicates	How many iterations of the randomisation should be done per species removal

Value

gives a dataset of values when you remove a species from a network, and the values obtained when randomising this subnetwork

Examples

mat <- matrix(nrow =10, ncol =10, sample(c(0,1), 100, prob = c(0.6, 0.4), replace = T))
removing_and_randomizing(network = mat, index = 'modularity', datatype = 'matrix')

hemprichbennett/netReducer documentation built on Aug. 11, 2019, 6:48 a.m.