Package: modEvA 3.20

A. Marcia Barbosa

modEvA: Model Evaluation and Analysis

Analyses species distribution models and evaluates their performance. It includes functions for variation partitioning, extracting variable importance, computing several metrics of model discrimination and calibration performance, optimizing prediction thresholds based on a number of criteria, performing multivariate environmental similarity surface (MESS) analysis, and displaying various analytical plots. Initially described in Barbosa et al. (2013) <doi:10.1111/ddi.12100>.

Authors:A. Marcia Barbosa [aut, cre], Jennifer A. Brown [aut], Alberto Jimenez-Valverde [aut], Raimundo Real [aut], Oswald van Ginkel [ctb], Jurica Levatic [ctb], Victoria Formoso-Freire [ctb], Andres Baselga [ctb], Carola Gomez-Rodriguez [ctb], Jose Carlos Guerrero [fnd]

modEvA_3.20.tar.gz
modEvA_3.20.tar.gz(r-4.5-noble)modEvA_3.20.tar.gz(r-4.4-noble)
modEvA_3.20.tgz(r-4.4-emscripten)modEvA_3.20.tgz(r-4.3-emscripten)
modEvA.pdf |modEvA.html✨
modEvA/json (API)
NEWS

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

Peer review:

Bug tracker:https://r-forge.r-project.org/projects/modeva

Datasets:

5.04 score 2 packages 239 scripts 1.3k downloads 19 mentions 39 exports 2 dependencies

Last updated 1 days agofrom:f45f8c820c. Checks:OK: 2. Indexed: no.

TargetResultDate
Doc / VignettesOKOct 30 2024
R-4.5-linuxOKOct 30 2024

Exports:applyThresholdarrangePlotsAUCBoyceconfusionLabelconfusionMatrixDsquarederrorMeasuresevaluateevennessgetBinsgetModEqngetThresholdHLfitinputMunchlogLikelollipopMESSMillerCalibmod2obspredmodEvAmethodsmultModEvOAoptiPairoptiThreshplotGLMpredDensitypredPlotprevalenceptsrast2obspredquantReclassrange01RMSERsqGLMsimilaritystandard01threshMeasuresvarImpvarPart

Dependencies:Rcppterra

Readme and manuals

Help Manual

Help pageTopics
Model Evaluation and AnalysismodEvA-package modEvA
Apply threshold(s) to model predictionsapplyThreshold
Arrange plotsarrangePlots
Area Under the CurveAUC
Boyce IndexBoyce
Label predictions according to their confusion matrix categoryconfusionLabel
Confusion matrixconfusionMatrix
Explained devianceDsquared
Measures of model prediction error.errorMeasures
Evaluate a model based on the elements of a confusion matrix.evaluate
Evenness in a binary vector.evenness
Get bins of continuous values.getBins
Get model equationgetModEqn
Prediction threshold for a given criteriongetThreshold
Hosmer-Lemeshow goodness of fitHLfit
Munch inputs into 'obs' and 'pred' vectorsinputMunch
Log-likelihoodlogLike
Lollipop chartlollipop
Multivariate Environmental Similarity Surfaces based on a data frameMESS
Miller's calibration satistics for logistic regression modelsMillerCalib
Extract observed and predicted values from a model object.mod2obspred
Methods implemented in modEvA functionsmodEvAmethods
Multiple model evaluationmultModEv
Overlap AnalysisOA
Optimize the classification threshold for a pair of related model evaluation measures.optiPair
Optimize threshold for model evaluation.optiThresh
Plot a generalized linear modelplotGLM
Plot the density of predicted or predictor values for presences and absences (or background)predDensity
Plot predicted values for presences and absences, optionally classified according to a prediction threshold.predPlot
Prevalenceprevalence
Observed and predicted values from presence points and a raster map.ptsrast2obspred
Reclassify continuous values based on quantilesquantReclass
Shrink or stretch a vector to make it range between 0 and 1range01
Root mean square errorRMSE
Rotifer distribution modelsrotif.mods
R-squared measures for GLMsRsqGLM
Similarity measuressimilarity
Standardize to 0-1 (or vice-versa)standard01
Threshold-based measures of model evaluationthreshMeasures
Variable importance.varImp
Variation partitioningvarPart