ROC: Build a ROC curve
In ModTools: Tools for Building Regression and Classification Models

Description Usage Arguments Details Value Author(s) References See Also Examples

This is a wrapper to the main function pROC of the pROC package (by Xavier Robin et al.). It builds a ROC curve and returns a "roc" object, a list of class "roc".

1	ROC(x, resp = NULL, ...)

`x`	a model object, or the predicted probabilities, when resp is not `NULL`.
`resp`	the response
`...`	all arguments are passed to `roc()`.

Partial ROC is calculated following Peterson et al. (2008; doi: 10.1016/j.ecolmodel.2007.11.008). This function is a modification of the PartialROC funcion, available at https://github.com/narayanibarve/ENMGadgets.

A data.frame containing the AUC values and AUC ratios calculated for each iteration.

Andri Signorell <andri@signorell.net>

Peterson, A.T. et al. (2008) Rethinking receiver operating characteristic analysis applications in ecological niche modeling. Ecol. Modell., 213, 63-72.

pROC

r.glm <- FitMod(diabetes ~ ., data = d.pima, fitfn="logit")
ROC(r.glm)

# plot ROC curves for a list of models
r.rp <- FitMod(diabetes ~ ., data = d.pima, fitfn="rpart")

# combine models to a list
mlst <- list(r.glm, r.rp)

# do the plot
for(i in seq_along(mlst))
  if(i==1){
    plot(ROC(mlst[[i]], grid=TRUE, col=c(hred, hblue)[i]))
  } else {
    lines(ROC(mlst[[i]], col=c(hred, hblue)[i]))
  }