Area Under Receiver Operating Characteristic Curve

Source: R/AUROC.R

Compare area under the receiver operating characteristic curve (AUROC) for binary (e.g., logistic) models. The area under the ROC curve provides a measure of the model's classification accuracy averaged over all possible threshold values.

AUROC(object, ...)

# S3 method for spglm
AUROC(object, ...)

# S3 method for spgautor
AUROC(object, ...)

Arguments

object

A fitted model object from spglm() or spgautor()) where family = "binomial" and the response values are binary, representing a single success or failure for each datum.

...

Additional arguments to pROC::auc().

Value

The area under the receiver operating characteristic curve.

References

Robin, X., Turck, N., Hainard, A., Tiberti, N., Lisacek, F., Sanchez, J. C., & Müller, M. (2011). pROC: an open-source package for R and S+ to analyze and compare ROC curves. BMC bioinformatics, 12, 1-8.

Examples

spgmod <- spglm(presence ~ elev,
  family = "binomial", data = moose,
  spcov_type = "exponential"
)
AUROC(spgmod)
#> [1] 0.9318182