Movement-based kernel density estimate (MKDE) in 3D using Rcpp

Share:

Description

Provides a function for 3-dimensional MKDEs.

Usage

1
mkde3Dgrid(mkde.obj, move.dat, t.step, d.thresh)	

Arguments

mkde.obj

A 3D MKDE object

move.dat

A move data object

t.step

An integration time step

d.thresh

A kernel density threshold

Details

This is lower-level function that call the C++ function. for estimating the movement-based density in 3D. In practice, users should call initializeDensity.
The argument d.thresh is a univariate probability density beyond which the kernel contribution to the overall MKDE is assumed to be negligible. Usually this is set at a very small value and is used to prevent calculations from being performed in cells to which the kernel makes a negligible contribution.

Value

An array whose elements are the estimated utilization probabilities for each voxel.

Author(s)

Jeff A. Tracey, PhD
USGS Western Ecological Research Center, San Diego Field Station
jatracey@usgs.gov
James Sheppard, PhD
San Diego Zoo Institute for Conservation Research
jsheppard@sandiegozoo.org
Robert Sinkovits, PhD
San Diego Supercomputer Center
sinkovit@sdsc.edu
Glenn Lockwood, PhD
San Diego Supercomputer Center
glock@sdsc.edu
Jun Zhu, PhD
University of Wisconsin-Madison
jzhu@stat.wisc.edu

Examples

 1
 2
 3
 4
 5
 6
 7
 8
 9
10
11
12
13
14
15
16
library(raster)
data(condor)
condor <- condor[1:10,] # simply to make example run more quickly
mv.dat <- initializeMovementData(condor$time, condor$x, condor$y, 
z.obs=condor$z, sig2obs=25.0, sig2obs.z=81.0, t.max=65.0)

data(condordem120)
cell.sz <- mean(res(condordem120))
ext <- extent(condordem120)
nx <- ncol(condordem120)
ny <- nrow(condordem120)
nz <- ceiling(3000.0/cell.sz)
mkde.obj <- initializeMKDE3D(ext@xmin, cell.sz, nx, ext@ymin, cell.sz,
ny, 0.0, cell.sz, nz)

res <- mkde3Dgrid(mkde.obj, mv.dat, 5.0, 1e-20)

Want to suggest features or report bugs for rdrr.io? Use the GitHub issue tracker.