Configurational entropy for point patterns

Source: R/bes_p_cushman.R

Calculates Cushman's configurational entropy for point patterns (2021)

bes_p_cushman(x, nr_of_permutations, independent = FALSE)

Arguments

x

SpatRaster, stars, RasterLayer, RasterStack, RasterBrick, matrix, or array containing one or more rasters with one value and NAs

nr_of_permutations

Number of permutations performed on each input raster to calculate possible distribution of the number of nearest neighbors

independent

Should an independent set of permutations be performed for each input raster? TRUE/FALSE. Use FALSE (default) when each of your input rasters has the same configuration.

Value

A tibble

References

Cushman, S. A. (2021). Generalizing Boltzmann Configurational Entropy to Surfaces, Point Patterns and Landscape Mosaics. In Entropy (Vol. 23, Issue 12, p. 1616). MDPI AG. https://doi.org/10.3390/e23121616

Examples

# \donttest{
  library(terra)
  library(bespatial)
  point_pattern = rast(system.file("raster/point_pattern.tif", package = "bespatial"))
  ce3 = bes_p_cushman(point_pattern, 100)
  plot(point_pattern, main = round(ce3$value, 2))

  ce3b = bes_p_cushman(point_pattern, 100, independent = TRUE)
  plot(point_pattern, main = round(ce3b$value, 2))

# }