Package: NLMR 1.1.1

Marco Sciaini

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 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.

Authors:Marco Sciaini [aut, cre], Matthias Fritsch [aut], Maximilian Hesselbarth [aut], Craig Simpkins [aut], Cédric Scherer [aut], Sebastian Hanß [aut], Laura Graham [rev], Jeffrey Hollister [rev]

NLMR_1.1.1.tar.gz
NLMR_1.1.1.zip(r-4.5)NLMR_1.1.1.zip(r-4.4)NLMR_1.1.1.zip(r-4.3)
NLMR_1.1.1.tgz(r-4.4-x86_64)NLMR_1.1.1.tgz(r-4.4-arm64)NLMR_1.1.1.tgz(r-4.3-x86_64)NLMR_1.1.1.tgz(r-4.3-arm64)
NLMR_1.1.1.tar.gz(r-4.5-noble)NLMR_1.1.1.tar.gz(r-4.4-noble)
NLMR_1.1.1.tgz(r-4.4-emscripten)NLMR_1.1.1.tgz(r-4.3-emscripten)
NLMR.pdf |NLMR.html
NLMR/json (API)
NEWS

# Install 'NLMR' in R:
install.packages('NLMR', repos = c('https://packages.ropensci.org', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/ropensci/nlmr/issues

Uses libs:
  • c++– GNU Standard C++ Library v3

On CRAN:

landscape-ecologyneutral-landscape-modelpeer-reviewedspatial

15 exports 65 stars 7.75 score 44 dependencies 4 mentions 195 scripts 110 downloads

Last updated 1 months agofrom:196dbfd2b1 (on master). Checks:OK: 1 NOTE: 8. Indexed: yes.

TargetResultDate
Doc / VignettesOKOct 02 2024
R-4.5-win-x86_64NOTEOct 02 2024
R-4.5-linux-x86_64NOTEOct 02 2024
R-4.4-win-x86_64NOTEOct 02 2024
R-4.4-mac-x86_64NOTEOct 02 2024
R-4.4-mac-aarch64NOTEOct 02 2024
R-4.3-win-x86_64NOTEOct 02 2024
R-4.3-mac-x86_64NOTEOct 02 2024
R-4.3-mac-aarch64NOTEOct 02 2024

Exports:nlm_curdsnlm_distancegradientnlm_edgegradientnlm_fbmnlm_gaussianfieldnlm_mosaicfieldnlm_mosaicgibbsnlm_mosaictessnlm_mpdnlm_neighnlm_percolationnlm_planargradientnlm_randomnlm_randomclusternlm_randomrectangularcluster

Dependencies:backportscheckmateclassclassIntcliDBIdeldirdplyre1071fansifasterizegenericsglueKernSmoothlatticelifecyclemagrittrMASSMatrixpillarpkgconfigpolyclipproxyR6rasterRcppRcppArmadillorlangs2sfspspatstat.dataspatstat.geomspatstat.randomspatstat.univarspatstat.utilsterratibbletidyselectunitsutf8vctrswithrwk

Basic Usage of NLMR

Rendered fromgetstarted.Rmdusingknitr::rmarkdownon Oct 02 2024.

Last update: 2019-02-27
Started: 2018-01-10

Readme and manuals

Help Manual

Help pageTopics
nlm_curdsnlm_curds
nlm_distancegradientnlm_distancegradient
nlm_edgegradientnlm_edgegradient
nlm_fbmnlm_fbm
nlm_gaussianfieldnlm_gaussianfield
nlm_mosaicfieldnlm_mosaicfield
nlm_mosaicgibbsnlm_mosaicgibbs
nlm_mosaictessnlm_mosaictess nlm_polylands
nlm_mpdnlm_mpd
nlm_neighnlm_neigh
nlm_percolationnlm_percolation
nlm_planargradientnlm_planargradient
nlm_randomnlm_random
nlm_randomclusternlm_randomcluster
nlm_randomrectangularclusternlm_randomrectangularcluster