Package: voluModel 0.2.5.9000

voluModel: Modeling Species Distributions in Three Dimensions

Facilitates modeling species' ecological niches and geographic distributions based on occurrences and environments that have a vertical as well as horizontal component, and projecting models into three-dimensional geographic space. Working in three dimensions is useful in an aquatic context when the organisms one wishes to model can be found across a wide range of depths in the water column. The package also contains functions to automatically generate marine training model training regions using machine learning, and interpolate and smooth patchily sampled environmental rasters using thin plate splines. Davis Rabosky AR, Cox CL, Rabosky DL, Title PO, Holmes IA, Feldman A, McGuire JA (2016) <doi:10.1038/ncomms11484>. Nychka D, Furrer R, Paige J, Sain S (2021) <doi:10.5065/D6W957CT>. Pateiro-Lopez B, Rodriguez-Casal A (2022) <https://CRAN.R-project.org/package=alphahull>.

Authors:Hannah L. Owens [aut, cre, cph], Emmaline Sheahan [aut], Carsten Rahbek [aut]

voluModel_0.2.5.9000.tar.gz
voluModel_0.2.5.9000.zip(r-4.7-any)voluModel_0.2.5.9000.zip(r-4.6-any)voluModel_0.2.5.9000.zip(r-4.5-any)
voluModel_0.2.5.9000.tgz(r-4.6-any)voluModel_0.2.5.9000.tgz(r-4.5-any)
voluModel_0.2.5.9000.tar.gz(r-4.7-any)voluModel_0.2.5.9000.tar.gz(r-4.6-any)
voluModel_0.2.5.9000.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
voluModel/json (API)

# Install 'voluModel' in R:
install.packages('voluModel', repos = c('https://hannahlowens.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/hannahlowens/volumodel/issues

Pkgdown/docs site:https://hannahlowens.github.io

On CRAN:

Conda:

6.70 score 12 stars 42 scripts 322 downloads 29 exports 99 dependencies

Last updated from:0284381dab. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develOK309
source / vignettesOK344
linux-releaseOK285
macos-releaseOK183
macos-oldrelOK207
windows-develOK217
windows-releaseOK192
windows-oldrelOK241
wasm-releaseOK164

Exports:areColorsblendColorbottomRastercenterPointRasterTemplatecleanDepthcolumnParsedepthMatchdiversityStackdownsampleenv_stack_transforminterpolateRastermarineBackgroundmaxent_3DMESS3DmSampling2DmSampling3DoneRasterPlotpartition_3DplotLayerspointCompMappointMaprasterCompsmoothRastertestIntersectionthreshold_3DtransectPlottranspColorverticalSamplexyzSample

Dependencies:abindalphahullaskpassbackportscachemcheckmateclassclassIntclicommonmarkcpp11curldata.tableDBIdeldirdigestdotCall64dplyre1071farverfastmapfieldsFormulaformula.toolsgenericsggplot2ggtextgluegridtextgtablehttrinterpisobandjpegjsonliteKernSmoothlabelinglatticelifecyclelitedownlubridatemagrittrmapsmarkdownMatrixmemoisemetRmimeopenssloperator.toolspbapplypillarpkgconfigplyrpngpolyclippredictsproxypurrrR.methodsS3R.ooR.utilsR6rangeBuilderRColorBrewerRcppRcppEigenrlangrnaturalearths2S7scalessfsgeostatspspamspatstat.dataspatstat.geomspatstat.randomspatstat.sparsespatstat.univarspatstat.utilssplancsstringistringrsystensorterratibbletidyselecttimechangeunitsutf8vctrsviridisLitewithrwkxfunxml2

Introduction to voluModel
Introduction | Data Inputs | A point about 3D environmental data extraction | Data sampling | Niche envelope models | Tidying up | References
Rendered froma_Introduction.Rmdusingknitr::rmarkdown

Last update: 2026-05-19
Started: 2022-02-14

Environmental Data Sampling
Introduction | 3D Data Extraction | Generating Repeatable Training Regions | Background Data Extraction | Tidying up | References
Rendered fromc_DataSampling.Rmdusingknitr::rmarkdown

Last update: 2026-05-19
Started: 2022-02-14

Visualization Tools
Introduction | Plotting points | Plotting rasters | Tidying up | References
Rendered fromd_Visualization.Rmdusingknitr::rmarkdown

Last update: 2026-05-19
Started: 2022-02-14

3D Niche Modeling with the GLM Algorithm
Introduction | Data Inputs | Sampling data for model generation | Generalized linear model | Cropping out extreme extrapolation | Tidying up | References
Rendered frome_GLMWorkflow.Rmdusingknitr::rmarkdown

Last update: 2026-05-19
Started: 2022-02-14

Processing Raster Data
Introduction | Data Inputs | Interpolation | Tidying up | References
Rendered fromb_RasterProcessing.Rmdusingknitr::rmarkdown

Last update: 2025-07-18
Started: 2022-02-14