Package: NLMR 1.2.0
Jakub Nowosad
NLMR: Simulating Neutral Landscape Models
Provides neutral landscape models (<doi:10.1007/BF02275262>, <https://sci-hub.in/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:
NLMR_1.2.0.tar.gz
NLMR_1.2.0.zip(r-4.7)NLMR_1.2.0.zip(r-4.6)NLMR_1.2.0.zip(r-4.5)
NLMR_1.2.0.tgz(r-4.6-x86_64)NLMR_1.2.0.tgz(r-4.6-arm64)NLMR_1.2.0.tgz(r-4.5-x86_64)NLMR_1.2.0.tgz(r-4.5-arm64)
NLMR_1.2.0.tar.gz(r-4.7-arm64)NLMR_1.2.0.tar.gz(r-4.7-x86_64)NLMR_1.2.0.tar.gz(r-4.6-arm64)NLMR_1.2.0.tar.gz(r-4.6-x86_64)
NLMR_1.2.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
NLMR/json (API)
NEWS
| # Install 'NLMR' in R: |
| install.packages('NLMR', repos = c('https://predictiveecology.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/ropensci/nlmr/issues
Pkgdown/docs site:https://docs.ropensci.org
landscape-ecologyneutral-landscape-modelpeer-reviewedspatialcpp
Last updated from:393db99722. Checks:13 OK. Indexed: no.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-arm64 | OK | 171 | ||
| linux-devel-x86_64 | OK | 225 | ||
| source / vignettes | OK | 242 | ||
| linux-release-arm64 | OK | 173 | ||
| linux-release-x86_64 | OK | 182 | ||
| macos-release-arm64 | OK | 100 | ||
| macos-release-x86_64 | OK | 438 | ||
| macos-oldrel-arm64 | OK | 116 | ||
| macos-oldrel-x86_64 | OK | 255 | ||
| windows-devel | OK | 187 | ||
| windows-release | OK | 153 | ||
| windows-oldrel | OK | 147 | ||
| wasm-release | OK | 142 |
Exports:nlm_curdsnlm_distancegradientnlm_edgegradientnlm_fbmnlm_gaussianfieldnlm_mosaicfieldnlm_mosaicgibbsnlm_mosaictessnlm_mpdnlm_neighnlm_percolationnlm_planargradientnlm_randomnlm_randomclusternlm_randomrectangularclusterutil_classify
Dependencies:backportscheckmateclassclassIntcliDBIdeldirdplyre1071fasterizegenericsglueKernSmoothlatticelifecyclemagrittrMASSMatrixpillarpkgconfigpolyclipproxyR6rasterRcppRcppArmadillorlangs2sfspspatstat.dataspatstat.geomspatstat.randomspatstat.univarspatstat.utilsterratibbletidyselectunitsutf8vctrswithrwk
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| nlm_curds | nlm_curds |
| nlm_distancegradient | nlm_distancegradient |
| nlm_edgegradient | nlm_edgegradient |
| nlm_fbm | nlm_fbm |
| nlm_gaussianfield | nlm_gaussianfield |
| nlm_mosaicfield | nlm_mosaicfield |
| nlm_mosaicgibbs | nlm_mosaicgibbs |
| nlm_mosaictess | nlm_mosaictess nlm_polylands |
| nlm_mpd | nlm_mpd |
| nlm_neigh | nlm_neigh |
| nlm_percolation | nlm_percolation |
| nlm_planargradient | nlm_planargradient |
| nlm_random | nlm_random |
| nlm_randomcluster | nlm_randomcluster |
| nlm_randomrectangularcluster | nlm_randomrectangularcluster |
| util_classify | util_classify util_classify.RasterLayer |
