| HWI {assocInd} | R Documentation |
Half-Weight Index
Description
Calculates the half-weight index
Usage
HWI(x, Ya, Yb, Yab)
Arguments
x |
Number of times individuals a and b were observed together |
Ya |
Number of times individual a was observed without b |
Yb |
Number of times individual b was observed without a |
Yab |
Number of times individuals a and b were observed at the same time but not associating |
Details
The half-weight index calculates the probability that two individuals are observed together given that one has been seen, but under the assumption that the probability of missing individuals a or b when they are together is equal to M times the probability of missing them when they are apart. This index is the most commonly used in animal social network analysis, but note that Hoppitt & Farine (in prep) and other authors argue that the weighting of the probabilities is arbitrary.
Value
Returns two elements: the estimated association strength and the standard error of the estimate.
Author(s)
William Hoppitt <W.J.E.Hoppitt@leeds.ac.uk> Damien Farine <dfarine@orn.mpg.de>
References
Hoppitt, W. & Farine, D.R. (in prep) Association indices for quantifying social relationships: how to deal with missing observations of individuals or groups.
Examples
# Simulated values (all = 10)
x <- ya <- yb <- yab <- 10
# Calculate half-weight index
HWI(x,ya,yb,yab)