`telemetry`

data and a corresponding continuous-time movement model.`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,...)

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

`UD`

s calculated on the same grid.`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.`bandwidth`

, `raster,UD-method`