ctmm (version 0.3.6)

akde: Calculate an autocorrelated kernel density estimate

Description

This function calculates autocorrelated kernel density home-range estimates from telemetry data and a corresponding continuous-time movement model.

Usage

akde(data,CTMM,VMM=NULL,debias=TRUE,smooth=TRUE,error=0.001,res=10,grid=NULL,...)
# S3 method for telemetry
akde(data,CTMM,VMM=NULL,debias=TRUE,smooth=TRUE,error=0.001,res=10,grid=NULL,...)
# S3 method for list
akde(data,CTMM,VMM=NULL,debias=TRUE,smooth=TRUE,error=0.001,res=10,grid=NULL,...)
# S3 method for UD
mean(x,...)

Arguments

data

2D timeseries telemetry data represented as a telemetry object or list of objects.

CTMM

A ctmm movement model from the output of ctmm.fit or list of objects.

VMM

An optional vertical ctmm object for 3D home-range calculation.

debias

Debias the distribution for area estimation (AKDEc).

smooth

"Smooth" out errors from the data.

error

Target probability error.

res

Number of grid points along each axis, relative to the bandwidth.

grid

Optional grid specification with columns labeled x and y. Not yet supported.

...

Arguments passed to all instances of bandwidth, such as weights.

x

A list of UDs calculated on the same grid.

Value

Returns a UD object: a list with the sampled grid line locations r$x and r$y, the extent of each grid cell dr, the probability density and cumulative distribution functions evaluated on the sampled grid locations PDF & CDF, the optimal bandwidth matrix H, and the effective sample size of the data in DOF.H.

For weighted AKDE, please note additional ... arguments passed to bandwidth and the weights=TRUE argument, specifically.

When feeding in lists of telemetry and ctmm objects, all UDs will be calculated on the same grid. These UDs can be averaged with the mean command, however this is not an optimal way to calculate population ranges.

References

C. H. Fleming and W. F. Fagan and T. Mueller and K. A. Olson and P. Leimgruber and J. M. Calabrese (2015). Rigorous home-range estimation with movement data: A new autocorrelated kernel-density estimator. Ecology, 96(5), 1182-1188.

C. H. Fleming, J. M. Calabrese, A new kernel-density estimator for accurate home-range and species-range area estimation, Methods in Ecology and Evolution, DOI:10.1111/2041-210X.12673 (2016).

See Also

bandwidth, raster,UD-method

Examples

# NOT RUN {
# Load package and data
library(ctmm)
data(buffalo)
cilla <- buffalo[[1]]

# Fit a continuous-velocity model with tau ~ c(10 days, 1 hour)
# see help(variogram.fit)
GUESS <- ctmm(tau=c(10*24*60^2,60^2))
FIT <- ctmm.fit(cilla,GUESS)

# Compute akde object
UD <- akde(cilla,FIT)

# Plot data with AKDE contours
plot(cilla,UD=UD)
# }