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modEvA (version 3.13.3)

Model Evaluation and Analysis

Description

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) .

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Version

Install

install.packages('modEvA')

Monthly Downloads

1,646

Version

3.13.3

License

GPL-3

Maintainer

A. Barbosa

Last Published

January 19th, 2024

Functions in modEvA (3.13.3)

getModEqn

Get model equation
getThreshold

Prediction threshold for a given criterion
confusionLabel

Label predictions according to their confusion matrix category
arrangePlots

Arrange plots
inputMunch

Munch inputs into 'obs' and 'pred' vectors
lollipop

Lollipop chart
optiPair

Optimize the classification threshold for a pair of related model evaluation measures.
evenness

Evenness in a binary vector.
getBins

Get bins of continuous values.
prevalence

Prevalence
range01

Shrink or stretch a vector to make it range between 0 and 1
predPlot

Plot predicted values for presences and absences, optionally classified according to a prediction threshold.
confusionMatrix

Confusion matrix
evaluate

Evaluate a model based on the elements of a confusion matrix.
rotif.mods

Rotifer distribution models
threshMeasures

Threshold-based measures of model evaluation
varImp

Variable importance.
optiThresh

Optimize threshold for model evaluation.
modEvAmethods

Methods implemented in modEvA functions
multModEv

Multiple model evaluation
similarity

Similarity measures
standard01

Standardize to 0-1 (or vice-versa)
plotGLM

Plot a generalized linear model
predDensity

Plot the density of predicted values for presences and absences.
varPart

Variation partitioning
mod2obspred

Extract observed and predicted values from a model object.
ptsrast2obspred

Observed and predicted values from presence points and a raster map.
modEvA-package

Model Evaluation and Analysis
quantReclass

Reclassify continuous values based on quantiles
MESS

Multivariate Environmental Similarity Surfaces based on a data frame
OA

Overlap Analysis
MillerCalib

Miller's calibration satistics for logistic regression models
RMSE

Root mean square error
Dsquared

Explained deviance
HLfit

Hosmer-Lemeshow goodness of fit
AUC

Area Under the Curve
Boyce

Boyce Index
RsqGLM

R-squared measures for GLMs
applyThreshold

Apply threshold(s) to model predictions