rhrAsymptote: Asymptote of a home-range estimate
In jmsigner/rhr: Reproducible Home Ranges with R

Description Usage Arguments Details Value References Examples

rhrAsymptote returns the sample size at which a home-range is reached, if it present.

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rhrAsymptote(x, ns = seq(nrow(rhrData(x))/10, nrow(rhrData(x)), length.out =
  10), nrep = 10, tolTotArea = 0.05, nTimes = 5,
  sampling = "sequential")

`x`	Object of class RhrEst, the home-range estimate for which the asymptote is calculated.
`ns`	Numeric vector, the sample sizes for which the bootstrap is performed.
`nrep`	Numeric value, number of bootstrap replicates for each sample size.
`tolTotArea`	Numeric value (greater than 0 and smaller than 1), tolerance to the total area (that is the area using all relocations).
`nTimes`	Numeric value, number of times the confidence interval is required to be within tolerated total area
`sampling`	Character value, either 'random' or 'sequential'. See below for details.

Bootstrapped home-range sizes are calculated for different sample sizes. Starting from ns[1] relocations until a maximum sample size ns[length(ns)] points. Home-range sizes are plotted against the sample sizes. Laver (2005, 2005) suggested to use the following cutoff value: the number of locations at which estimates of the 95 % confidence interval of the bootstrapped home-range area is within a specified percentage of the total home range area (that is the area of the home range with all relocations) for at least nTimes times. Harris 1990 suggested to use random sampling for discontinuous radio tracking data and sequential sampling for continuous radio tracking data.

An object of class RhrHRAsymptote

Harris, S., et al. "Home-range analysis using radio-tracking data-a review of problems and techniques particularly as applied to the study of mammals." Mammal review 20.2-3 (1990): 97-123.

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

data(datSH)

## With MCP
## Not run: 
mcp <- rhrMCP(datSH[, 2:3])
mcpA <- rhrAsymptote(mcp)
plot(mcpA)

# maybe increase ns
# how many samples do we have?
nrow(datSH)
ns <- seq(20, nrow(datSH), 10)
mcpA <- rhrAsymptote(mcp, ns = ns)
plot(mcpA)
mcpA

# An asymptote is reached, but it seems that there is more structure in the
# data
# Lets have a look at the dates when the fixes were recorded
library(lubridate)
datSH$day <- ymd(datSH$day)
table(year(datSH$day))
# Lets only look at fixes from the first year
d1 <- datSH[year(datSH$day) == 2008, ]
nrow(d1)
ns <- seq(20, nrow(d1), 10)
mcp <- rhrMCP(d1[, 2:3])
mcpA <- rhrAsymptote(mcp, ns = ns)
plot(mcpA)
mcpA

## End(Not run)