Package: itsdm 0.2.1

Lei Song

itsdm: Isolation Forest-Based Presence-Only Species Distribution Modeling

Collection of R functions to do purely presence-only species distribution modeling with isolation forest (iForest) and its variations such as Extended isolation forest and SCiForest. See the details of these methods in references: Liu, F.T., Ting, K.M. and Zhou, Z.H. (2008) <doi:10.1109/ICDM.2008.17>, Hariri, S., Kind, M.C. and Brunner, R.J. (2019) <doi:10.1109/TKDE.2019.2947676>, Liu, F.T., Ting, K.M. and Zhou, Z.H. (2010) <doi:10.1007/978-3-642-15883-4_18>, Guha, S., Mishra, N., Roy, G. and Schrijvers, O. (2016) <https://proceedings.mlr.press/v48/guha16.html>, Cortes, D. (2021) <arxiv:2110.13402>. Additionally, Shapley values are used to explain model inputs and outputs. See details in references: Shapley, L.S. (1953) <doi:10.1515/9781400881970-018>, Lundberg, S.M. and Lee, S.I. (2017) <https://dl.acm.org/doi/abs/10.5555/3295222.3295230>, Molnar, C. (2020) <ISBN:978-0-244-76852-2>, Štrumbelj, E. and Kononenko, I. (2014) <doi:10.1007/s10115-013-0679-x>. itsdm also provides functions to diagnose variable response, analyze variable importance, draw spatial dependence of variables and examine variable contribution. As utilities, the package includes a few functions to download bioclimatic variables including 'WorldClim' version 2.0 (see Fick, S.E. and Hijmans, R.J. (2017) <doi:10.1002/joc.5086>) and 'CMCC-BioClimInd' (see Noce, S., Caporaso, L. and Santini, M. (2020) <doi:10.1038/s41597-020-00726-5>.

Authors:Lei Song [aut, cre], Lyndon Estes [ths]

itsdm_0.2.1.tar.gz
itsdm_0.2.1.zip(r-4.5)itsdm_0.2.1.zip(r-4.4)itsdm_0.2.1.zip(r-4.3)
itsdm_0.2.1.tgz(r-4.4-any)itsdm_0.2.1.tgz(r-4.3-any)
itsdm_0.2.1.tar.gz(r-4.5-noble)itsdm_0.2.1.tar.gz(r-4.4-noble)
itsdm_0.2.1.tgz(r-4.4-emscripten)itsdm_0.2.1.tgz(r-4.3-emscripten)
itsdm.pdf |itsdm.html
itsdm/json (API)
NEWS

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

Peer review:

Bug tracker:https://github.com/lleisong/itsdm/issues

Datasets:

On CRAN:

isolation-forestoutlier-detectionpresence-onlymodelshapley-valuespecies-distribution-modelling

5.59 score 4 stars 65 scripts 209 downloads 19 exports 63 dependencies

Last updated 1 years agofrom:14fb9c83b4. Checks:OK: 1 NOTE: 6. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 02 2024
R-4.5-winNOTENov 02 2024
R-4.5-linuxNOTENov 02 2024
R-4.4-winNOTENov 02 2024
R-4.4-macNOTENov 02 2024
R-4.3-winNOTENov 02 2024
R-4.3-macNOTENov 02 2024

Exports:cmcc_bioclimconvert_to_padetect_envi_changedim_reduceevaluate_poformat_observationfuture_cmcc_bioclimfuture_worldclim2independent_responseisotree_pomarginal_responseprobabilityshap_dependenceshap_spatial_responsespatial_responsesuspicious_env_outliersvariable_analysisvariable_contribworldclim2

Dependencies:abindbackportscheckmateclassclassIntclicodetoolscolorspaceDBIdplyre1071fansifarverfastshapforeachgenericsggplot2gluegtableisobandisotreeiteratorsjsonliteKernSmoothlabelinglatticelifecyclemagrittrMASSMatrixmgcvmunsellncdf4nlmeoutliertreepatchworkpillarpkgconfigproxyR6rasterRcerealRColorBrewerRcppRcppArmadillorlangROCits2scalessfspstarsstringistringrterratibbletidyselectunitsutf8vctrsviridisLitewithrwk

Applications of Shapley values on SDM explanation

Rendered fromshap_application.Rmdusingknitr::rmarkdown_notangleon Nov 02 2024.

Last update: 2022-12-01
Started: 2022-12-01

Introduction of itsdm with a virtual species

Rendered fromintroduction_of_itsdm.Rmdusingknitr::rmarkdown_notangleon Nov 02 2024.

Last update: 2022-11-16
Started: 2021-11-11

Using itsdm to a real species: Africa savanna elephant

Rendered fromitsdm_example.Rmdusingknitr::rmarkdown_notangleon Nov 02 2024.

Last update: 2022-11-16
Started: 2022-01-03

Readme and manuals

Help Manual

Help pageTopics
Isolation forest-based presence-only species distribution modelingitsdm-package itsdm
Download historic Bioclimatic indicators (BIOs) named CMCC-BioClimInd.cmcc_bioclim
Convert predicted suitability to presence-absence map.convert_to_pa
Detect areas influenced by a changing environment variable.detect_envi_change
Remove environmental variables that have high correlation with others.dim_reduce
Evaluate the model based on presence-only data.evaluate_po
Format the occurrence dataset for usage in 'itsdm'format_observation
Download future Bioclimatic indicators (BIOs) named CMCC-BioClimInd.future_cmcc_bioclim
A function to parse the future climate from worldclim version 2.1.future_worldclim2
Calculate independent responses of each variables.independent_response
Build Isolation forest species distribution model and explain the the model and outputs.isotree_po
Boundary of mainland Africamainland_africa
Calculate marginal responses of each variables.marginal_response
Occurrence dataset of a virtual speciesocc_virtual_species
Display the figure and map of the 'EnviChange' object.plot.EnviChange
Exhibit suspicious outliers in an observation dataset.plot.EnvironmentalOutlier
Show independent response curves.plot.IndependentResponse
Show marginal response curves.plot.MarginalResponse
Display results of conversion to presence-absence (PA).plot.PAConversion
Show model evaluation.plot.POEvaluation
Show variable dependence plots and variable interaction plots obtained from Shapley values.plot.ShapDependence
Display Shapley values-based spatial variable dependence maps.plot.SHAPSpatial
Display spatial variable dependence maps.plot.SpatialResponse
Display variable importance.plot.VariableAnalysis
Exhibit variable contribution for target observations.plot.VariableContribution
Print summary information from 'EnviChange' object.print.EnviChange
Print summary information from 'EnvironmentalOutlier' object.print.EnvironmentalOutlier
Print summary information from 'FormatOccurrence' object.print.FormatOccurrence
Print summary information from 'PAConversion' object.print.PAConversion
Print summary information from model evaluation object ('POEvaluation').print.POEvaluation
Print summary information from 'POIsotree' object.print.POIsotree
Print summary information from 'ReducedImageStack' object.print.ReducedImageStack
Print summary information from variable importance object ('VariableAnalysis').print.VariableAnalysis
Estimate suitability on 'stars' object using trained 'isolation.forest' model.probability
Calculate Shapley value-based variable dependence.shap_dependence
Calculate shapley values-based spatial response.shap_spatial_response
Calculate spatial response or dependence figures.spatial_response
Function to detect suspicious outliers based on environmental variables.suspicious_env_outliers
Function to evaluate relative importance of each variable.variable_analysis
Evaluate variable contributions for targeted observations.variable_contrib
Download environmental variables made by worldclim version 2.1.worldclim2