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

## Description

Must be created for all subsequent plot function calls.

## Usage

 `1` ```makeRBPObj(pred, y, positive = NULL) ```

## Arguments

 `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".

## Value

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.

RBPcurve documentation built on May 29, 2017, 9:05 a.m.