makeRBPObj: Create data container for RBP curve.
In RBPcurve: The Residual-Based Predictiveness Curve

Must be created for all subsequent plot function calls.

1	makeRBPObj(pred, y, positive = NULL)

`pred`	[`numeric`] Predicted probabilities for each observation.
`y`	[`numeric` \| `factor`] Class labels of the target variable. Either a numeric vector with values `0` or `1`, or a factor with two levels.
`positive`	[`character(1)`] Set positive class label for target variable which is transformed as `1` to compute. Only needed when `y` is a "factor".

Object members:

n [numeric(1)]: Number of observations.
pred [numeric(n)]: Predicted probabilities.
y [numeric(n)]: Target variable having the values 0 and 1.
positive [character(1)]: Positive class label of traget variable. Only present when y is a factor.
e0 [numeric(1)]: Average of the predicted probabilities conditional on y=0.
e1 [numeric(1)]: Average of the predicted probabilities conditional on y=1.
pev [numeric(1)]: Proportion of explained variation measure. Computed as e1-e0.
tpr [numeric(1)]: True positive rate.
fpr [numeric(1)]: False positive rate.
prev [numeric(1)]: Prevalence.
one.min.prev [numeric(1)]: One minus the value of the prevalence.
axis.x [numeric(n)]: Values for the X-Axis of the RBP curve.
axis.y [numeric(n)]: Values for the Y-Axis of the RBP curve.