redistribution_kernel: Create a redistribution kernel

Description

From a fitted integrated step-selection function for a given position a redistribution kernel is calculated (i.e., the product of the movement kernel and the selection function).

Usage

redistribution_kernel(
  x = make_issf_model(),
  start = make_start(),
  map,
  fun = function(xy, map) {
     extract_covariates(xy, map, where = "both")
 },
  covars = NULL,
  max.dist = get_max_dist(x),
  n.control = 1e+06,
  n.sample = 1,
  landscape = "continuous",
  compensate.movement = landscape == "discrete",
  normalize = TRUE,
  interpolate = FALSE,
  as.rast = FALSE,
  tolerance.outside = 0
)

Arguments

x: [fit_issf]
A fitted integrated step-selection function. Generated either with fit_issf() or make make_issf_model().
start: [sim_start]
The start position in space and time. See make_start().
map: [SpatRaster]
A SpatRaster with all covariates.
fun: [function]
A function that is executed on each location of the redistribution kernel. The default function is extract_covariates().
covars: [tibble]
Additional covariates that might be used in the model (e.g., time of day).
max.dist: [numeric(1)]
The maximum distance of the redistribution kernel.
n.control: [integer(1)]{1e6}
The number of points of the redistribution kernel (this is only important if landscape = "continuous").
n.sample: [integer(1)]{1}
The number of points sampled from the redistribution kernel (this is only important if as.rast = FALSE).
landscape: [character(1)]{"continuous"}
If "continuous the redistribution kernel is sampled using a random sample of size n.control. If landscape = "discrete" each cell in the redistribution kernel is used.
compensate.movement: [logical(1)]
Indicates if movement parameters are corrected or not. This only relevant if landscape = 'discrete'.
normalize: [logical(1)]{TRUE}
If TRUE the redistribution kernel is normalized to sum to one.
interpolate: [logical(1)]{FALSE}
If TRUE a stochastic redistribution kernel is interpolated to return a raster layer. Note, this is just for completeness and is computationally inefficient in most situations.
as.rast: [logical(1)]{TRUE}
If TRUE a SpatRaster should be returned.
tolerance.outside: [numeric(1)]{0}
The proportion of the redistribution kernel that is allowed to be outside the map.