Model Evaluation and Analysis

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Documentation for package ‘modEvA’ version 3.39

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modEvA-package Model Evaluation and Analysis
applyThreshold Apply threshold(s) to model predictions
arrangePlots Arrange plots
AUC Area Under the Curve
Boyce Boyce Index
confusionLabel Label predictions according to their confusion matrix category
confusionMatrix Confusion matrix
Dsquared Explained deviance
errorMeasures Measures of model prediction error.
evaluate Evaluate a model based on the elements of a confusion matrix.
evenness Evenness in a binary vector.
getBins Get bins of continuous values.
getModEqn Get model equation
getThreshold Prediction threshold for a given criterion
HLfit Hosmer-Lemeshow goodness of fit
inputMunch Munch inputs into 'obs' and 'pred' vectors
logLike Log-likelihood
lollipop Lollipop chart
MESS Multivariate Environmental Similarity Surfaces based on a data frame
MillerCalib Miller's calibration satistics for logistic regression models
mod2obspred Extract observed and predicted, or predictor, values from a model object.
modEvA Model Evaluation and Analysis
modEvAmethods Methods implemented in modEvA functions
multModEv Multiple model evaluation
OA Overlap Analysis
optiPair Optimize the classification threshold for a pair of related model evaluation measures.
optiThresh Optimize threshold for model evaluation.
plotCoeffs Plot model coefficients with confidence intervals
plotGLM Plot a generalized linear model
predDensity Plot the density of predicted or predictor values for presences and absences (or background)
predPlot Plot predicted values for presences and absences, optionally classified according to a prediction threshold.
prevalence Prevalence
pseudoRsq Pseudo-R-squared measures for binary-response models
ptsrast2obspred Observed and predicted values from presence points and a raster map.
quantReclass Reclassify continuous values based on quantiles
range01 Shrink or stretch a vector to make it range between 0 and 1
RMSE Root mean square error
rotif.mods Rotifer distribution models
RsqGLM R-squared measures for GLMs
similarity Similarity measures
standard01 Standardize to 0-1 (or vice-versa)
threshMeasures Threshold-based measures of model evaluation
varImp Variable importance.
varPart Variation partitioning