rhrAsymptote: Calculate home rnage asymptote for an object of class...

Description Usage Arguments Value Note References Examples

Description

calculate home range asymptote

Usage

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  rhrAsymptote(x, ns = seq(100, nrow(dat(x)), 500),
    nrep = 10, tolTotArea = 0.05, nTimes = 5,
    sampling = "sequential")

Arguments

x

RhrHREstimator object

ns

numeric vector of the number of samples to be taken at each step

nrep

the number of replicates for each sample size

tolTotArea

tolerance to the total area (that is the area using all points)

nTimes

the number of times the confidence interval is required to be within tolerated total area

sampling

this should be either random or sequential. See notes for details.

Value

An object of class RhrHRAsymptote

Note

Bootstrapped home ranges are calculated for different sample sizes. Starting from very few samples until the sample size approaches the total number of points. Home range sizes are then plotted against the sample sizes. Laver (2005, 2005) suggested to use the following cutoff value: the number of location estimates at which the 95 % confidence interval of the bootstrapped home-range estimates is within a specified percentage of the total home range size (that is the size of the home range with all relocations) for at least n times. Harris 1990 suggested to use random sampling for discontinuous radio tracking data and sequential sampling for continuous radio tracking data.

References

Peter N Laver. Cheetah of the serengeti plains: a home range analysis. Master's thesis, Virginia Polytechnic Institute and State University, 2005

Peter N. Laver and Marcella J. Kelly. A critical review of home range studies. The Journal of Wildlife Management, 72(1):290-298, 2008

Examples

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## Not run: 
## calculate home range asymptote for kernel density estimation
## first calculate the home range
data(datSH)
hr <- rhrKDE(datSH[, 2:3], h="href")
hra <- rhrAsymptote(hr)
plot(hra)

## End(Not run)

rhr documentation built on May 2, 2019, 6:06 p.m.

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