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,debias=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.
debias
Debias the distribution for area estimation.
error
Target error for kernel truncation.
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.
Value
UD object: a list with the sampled grid line locations x and y, the area of each grid cell dA, 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.