Movement-based kernel density estimate (MKDE) in 2D using Rcpp
Provides a function for 2-dimensional MKDEs.
mkde2Dgrid(mkde.obj, move.dat, t.step, d.thresh)
mkde.obj |
A 2D or 2.5D MKDE object |
move.dat |
A move data object |
t.step |
An integration time step |
d.thresh |
A kernel density threshold |
This is lower-level function that call the C++ function. for
estimating the movement-based density in 2D. 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.
An array whose elements are the estimated utilization probabilities for each cell.
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
library(raster) data(panda) mv.dat <- initializeMovementData(panda$time, panda$x, panda$y, t.max=185.0, sig2obs=25.0) mv.dat <- initializeMovementData(panda$time, panda$x, panda$y, sig2obs=25.0, t.max=185.0) data(pandadem) cell.sz <- mean(res(pandadem)) ext <- extent(pandadem) nx <- ncol(pandadem) ny <- nrow(pandadem) mkde.obj <- initializeMKDE2D(ext@xmin, cell.sz, nx, ext@ymin, cell.sz, ny) res <- mkde2Dgrid(mkde.obj, mv.dat, 10.0, 1e-20)
Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.