Learn R Programming

ctmm (version 0.3.3)

akde: Calculate an autocorrelated kernel density estimate

Description

This function calculates autocorrelated kernel density estimates of different confidence levels from telemetry data and a continuous-time movement model.

Usage

akde(data,CTMM,VMM=NULL,debias=TRUE,smooth=TRUE,error=0.001,res=10,grid=NULL,...)

Arguments

data
2D timeseries telemetry data represented as a telemetry object.
CTMM
A ctmm movement model from the output of ctmm.fit.
VMM
An optional vertical ctmm object for 3D home-range calculation.
debias
Debias the distribution for area estimation.
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 akde.bandwidth.

Value

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.

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.

See Also

akde.bandwidth, raster,UD-method