The AUC function, in the modEvA package, initially computed only the area under the receiver operating characteristic (ROC) curve. Now, since modEvA version 1.7 (currently available on R-Forge), it also offers the option to compute the precision-recall curve, which may be better for comparing models based on imbalanced data (e.g. for rare species) — see e.g. Sofaer et al. (2019).

Usage example:

library(modEvA)
mod <- rotif.mods$models[["Ktropi"]]
par(mfrow = c(1, 2))
AUC(mod, main = "ROC curve")
AUC(mod, curve = "PR", main = "Precision-recall curve")

References

Sofaer, H.R., Hoeting, J.A. & Jarnevich, C.S. (2019). The area under the precision-recall curve as a performance metric for rare binary events. Methods in Ecology and Evolution, 10: 565-577

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