| NOSM_POT_undir {nos} | R Documentation |
Compute NOS using an undirected network and with a user provided network of potential interactions
Description
Computation of NOS using an undirected network (e.g. a social co-occurence network) and with a user provided network of potential interactions. In an undirected network, all nodes are considered as potential interacting partners.
Usage
NOSM_POT_undir(net, pot_net, perc = 1, sl = 1)
Arguments
net |
A network, in the form of an edge list. This should be a matrix or
dataframe with two columns. Each value in a column is a node. Nodes can be
identified using numbers or characters.Data can also be in the format of a
frequency interaction matrix, as used in the bipartite R
package. In these cases |
pot_net |
A network of all potential interactions. These should include, as a minimum, all the observed interactions (i.e. all links in net),plus any other possible interaction (such as all those permitted by a certain trophic rule). pot_net should have the same structure as net (e.g. it should be a data frame or matrix). |
perc |
(default to 1) - the fraction of node pair comparisons to be performed to compute NOS. We recommend performing all possible pair comparisons (perc = 1). However, for exploratory analyses on large sets of networks (or for very large networks), the possibility of using a lower fraction of pair comparisons is a useful option. |
sl |
(default is 1) Specifies whether cannibalistic interactions should be considered as possible and therefore taken into account and removed during computation ('1') or not ('0'). |
Value
A list of class 'NOSM' with a 'Type' attribute 'Pot_undir',
containing a vector of overlap values. The summary.NOSM
methods provides more useful summary statistics.
Examples
data(boreal)
y <- boreal[1:300,] #subset 300 rows for speed
d <- sample(nrow(y), 200, replace = FALSE) #create a random pot_net
pot_net <- y[d,] #by randomly sampling 200 rows from boreal
x <- NOSM_POT_undir(y, pot_net, perc = 1, sl = 1)
summary(x)