lhs.pep.add: Add hull metrics for proportion of enclosed points by each...

In tlocoh: Constructs homeranges and explores time use patterns from location data

Description

Computes proportion of enclosed points of a second set of points

Usage

lhs.pep.add(lhs, pep.var, pep.val = NULL, npep = TRUE, status = TRUE)

Arguments

lhs	A LoCoH-hullset object
pep.var	Name(s) of ancillary variable(s) saved with the LoCoH-hullset.
pep.val	Vector of value(s) for which the percentage of enclosed points will be calculated. If NULL, all unique values of pep.var will be used.
npep	Whether to compute the normalized proportion of enclosed points hull metric (normalized by the proportion of points in the entire dataset), T/F
status	Show messages, T/F

Value

A LoCoH-hullset object

Note

The proportion of enclosed points is a hull metric that measures relative association among N individuals when you have movement data for multiple individuals simultaneous over the same tim period. The general idea is to create hulls for all of the locations combined (ignoring which location was for each individual), then for each hull look at the proportion of enclosed points for each individual. If the individuals ignored each other, one would expect the proportion of enclosed points for any given hull to be approximately equal to the proportions of each individual in the entire dataset. Deviations from this random mixing null model reflect places where the individuals did not mix evenly (e.g., one dominated).

Do compute pep, all points must have the same id (beause you create hulls with the combined dataset) with the original id values saved as an ancillary variable (see lxy.id.new). Create hulls as you normally would using the 'a' or 'k' method, although it would be recommneded to omit time (let s=0) because the time difference between locations means different things for different pairs of points depending on whether they are from the same or different individuals. Pass the name of the ancillary variable that contains the original ids as pep.var and the original id value(s) as pep.val (if pep.val is omitted the pep metric will be computed for all id values found in pep.var. npep (normalized proportion of enclosed points) normalizes pep by the proportion of that individual in the entire dataset, such that npep=1 means the individual was in the hull in the same proportion as it was in the entire dataset. '

See Also

lxy.id.new

tlocoh documentation built on May 2, 2019, 5:27 p.m.