Add Contingency Matricies, ROC/AUROC

[hmrtn]

ROC and AUROC are important for determining the model skill. In doing so, we will need a consistent method for calculating confusion matrices.

• [x] Create confusion matrix function
• [x] Function for ROC and AUROC plots and data

[jonathancallahan]

I would like all of these function names to be prepended with skill_ so they are easy to find when reviewing the list of available functions.

After some googling I am now comfortably convinced that we should usecaret::confusionMatrix() as our base implementation of the confusion matrix and then build any higher level metrics we need from the components found in object returned by caret::confusionMatrix().

As with the move to the Raster package, we should stop rolling our own and just adopt caret as it appears to be full featured and well supported.

[hmrtn]

The functionality is based largely on the caret package and reproduces the same results but follows our data model a little more closesly.