Simulating Neutral Landscape Models

Provides neutral landscape models (, < http://sci-hub.tw/10.1007/bf02275262>). Neutral landscape models range from "hard" neutral models (completely random distributed), to "soft" neutral models (definable spatial characteristics) and generate landscape patterns that are independent of ecological processes. Thus, these patterns can be used as null models in landscape ecology. 'NLMR' combines a large number of algorithms from other published software for simulating neutral landscapes. The simulation results are obtained in a spatial data format (raster* objects from the 'raster' package) and can, therefore, be used in any sort of raster data operation that is performed with standard observation data.


Reference manual

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install.packages("NLMR")

1.1 by Marco Sciaini, 5 years ago


https://ropensci.github.io/NLMR/


Report a bug at https://github.com/ropensci/NLMR/issues/


Browse source code at https://github.com/cran/NLMR


Authors: Marco Sciaini [aut, cre] , Matthias Fritsch [aut] , Maximilian Hesselbarth [aut] , Craig Simpkins [aut] , Cédric Scherer [aut] , Sebastian Hanß [aut] , Laura Graham [rev] (Laura reviewed the package for rOpenSci , see https://github.com/ropensci/onboarding/issues/188) , Jeffrey Hollister [rev] (Jeffrey reviewed the package for rOpenSci , see https://github.com/ropensci/onboarding/issues/188)


Documentation:   PDF Manual  


GPL-3 license


Imports checkmate, dplyr, RandomFields, raster, spatstat.core, spatstat.geom, igraph, stats, tibble, fasterize, sf, Rcpp

Suggests testthat, covr, knitr, rmarkdown, lintr, landscapetools

Linking to Rcpp

System requirements: C++11


See at CRAN