NLMR: Simulating Neutral Landscape Models

Provides neutral landscape models (<doi:10.1007/BF02275262>, <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 geospatial 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.

Version:	1.0
Depends:	R (≥ 3.1.0)
Imports:	checkmate, dplyr, RandomFields, raster, spatstat, stats, tibble, fasterize, sf, Rcpp
LinkingTo:	Rcpp
Suggests:	testthat, covr, captioner, knitr, rmarkdown, lintr, landscapetools, igraph
Published:	2020-01-23
Author:	Marco Sciaini [aut, cre], Matthias Fritsch [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)
Maintainer:	Marco Sciaini <sciaini.marco at gmail.com>
BugReports:	https://github.com/ropensci/NLMR/issues/
License:	GPL-3
URL:	https://ropensci.github.io/NLMR/
NeedsCompilation:	yes
SystemRequirements:	C++11
Citation:	NLMR citation info
Materials:	NEWS
CRAN checks:	NLMR results

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