Package: webSDM 1.1-5

webSDM: Including Known Interactions in Species Distribution Models

A collection of tools to fit and work with trophic Species Distribution Models. Trophic Species Distribution Models combine knowledge of trophic interactions with Bayesian structural equation models that model each species as a function of its prey (or predators) and environmental conditions. It exploits the topological ordering of the known trophic interaction network to predict species distribution in space and/or time, where the prey (or predator) distribution is unavailable. The method implemented by the package is described in Poggiato, Andréoletti, Pollock and Thuiller (2022) <doi:10.22541/au.166853394.45823739/v1>.

Authors:Giovanni Poggiato [aut, cre, cph], Jérémy Andréoletti [aut]

webSDM_1.1-5.tar.gz
webSDM_1.1-5.zip(r-4.7-any)webSDM_1.1-5.zip(r-4.6-any)webSDM_1.1-5.zip(r-4.5-any)
webSDM_1.1-5.tgz(r-4.6-any)webSDM_1.1-5.tgz(r-4.5-any)
webSDM_1.1-5.tar.gz(r-4.7-any)webSDM_1.1-5.tar.gz(r-4.6-any)
webSDM_1.1-5.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
webSDM/json (API)

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

Bug tracker:https://github.com/giopogg/websdm/issues

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

Datasets:
  • G - Simulated environemntal covariates G
  • X - Simulated environmental covariates X
  • Y - Simulated species distribution Y

On CRAN:

Conda:

5.50 score 19 stars 11 scripts 347 downloads 8 exports 153 dependencies

Last updated from:ec86bf9f60. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develOK448
source / vignettesOK401
linux-releaseOK401
macos-releaseOK331
macos-oldrelOK323
windows-develOK420
windows-releaseOK400
windows-oldrelOK409
wasm-releaseOK181

Exports:computeVariableImportanceevaluateModelFitplotGplotG_inferredpredictPotentialSDMfittrophicSDMtrophicSDM_CV

Dependencies:abindbackportsbase64encbayesplotBHbootbridgesamplingbrmsBrobdingnagbroombroom.mixedbslibcachemcallrcheckmateclicodacodetoolscolourpickercommonmarkcpp11crayoncrosstalkdescdigestdismodistributionaldplyrDTdygraphsevaluatefarverfastmapfontawesomeforcatsforeachfsfurrrfuturefuture.applygenericsGGallyggdistggplot2ggridgesggstatsglmnetglobalsgluegridExtragtablegtoolshighrhmshtmltoolshtmlwidgetshttpuvigraphinlineisobanditeratorsjquerylibjsonlitejtoolsknitrlabelinglaterlatticelazyevallifecyclelistenvlitedownlme4loomagrittrmarkdownMASSMatrixmatrixStatsmemoisemgcvmimeminiUIminqamvtnormnleqslvnlmenloptrnumDerivotelpanderparallellypatchworkpillarpkgbuildpkgconfigplyrposteriorprettyunitsprocessxprogresspromisespspurrrquadprogQuickJSRR6rappdirsrasterrbibutilsRColorBrewerRcppRcppEigenRcppParallelRdpackreformulasreshape2rlangrmarkdownrstanrstanarmrstantoolsS7sandwichsassscalesshapeshinyshinyjsshinystanshinythemessourcetoolsspStanHeadersstringistringrsurvivaltensorAterrathreejstibbletidyrtidyselecttinytexutf8vctrsviridisLitewithrxfunxtablextsyamlzoo

Introduction to trophic SDM
Install and load webSDM | Simulate data | Create trophic interaction network | Fit trophic SDM | A trophicSDMfit object | Analyse a fitted trophicSDM | MCMC convergence | Parameter estimates and interpretation | Analysis of local models | Predictions with trophic SDM | Model evaluation | AIC, loo | Interpolation | Cross-validation | Potential niche | Author | References
Rendered fromIntroduction.Rmdusingknitr::rmarkdown

Last update: 2023-09-18
Started: 2022-10-23

Subtle and obvious differences between SDM and trophic SDM
Compare trophic and classical SDMs: difference and equalities | The simplest case | Simulation | Does this always hold? | Non-linear relationship between prey and predator | Non-continuous observable entities (presence-absence, counts) | Simulations | Non-linear statistical model
Rendered fromDifferences_with_SDMs.Rmdusingknitr::rmarkdown

Last update: 2023-09-18
Started: 2022-11-08

Composite variables and biotic-abiotic interactions
Composite variables | Composite variables and groups of preys | Custom formula | On computeVariableImportance with composite variable | Interaction with biotic and abiotic terms
Rendered fromComposite_variables.Rmdusingknitr::rmarkdown

Last update: 2022-11-21
Started: 2022-11-13