calibrate: External probability calibration

In bgreenwell/calibrater: Calibration Plots and Lift Charts for Binary Outcomes

Description

Validates predicted probabilities against a set of observed (binary) outcomes.

Usage

calibrate(
  prob,
  y,
  method = c("pratt", "iso", "ns"),
  pos.class = NULL,
  probs = c(0.05, 0.35, 0.65, 0.95)
)

## S3 method for class 'calibrate'
print(x, ...)

## S3 method for class 'calibrate'
plot(x, refline.col = "red", refline.lty = "dashed", refline.lwd = 1, ...)

Arguments

prob	Vector of predicted probabilities.
y	Vector of binary (i.e., 0/1) outcomes. If y is coded as anything other than 0/1, then you must specify which of the two categories represents the "positive" class (i.e., the class for which the probabilities specified in prob correspond to) via the pos.class argument.
method	Character string specifying which calibration method to use. Current options include: "pratt" Pratt scaling. "iso" Isotonic (i.e., monotonic) calibration. "ns" Natural (i.e., restricted) cubic splines; essentially, a spline-based nonparametric version of Pratt scaling.
pos.class	Numeric/character string specifying which values in y correspond to the "positive" class. Default is NULL. (Must be specified whenever y is not coded as 0/1., where 1 is assumed to represent the "positive" class.)
probs	Numeric vector specifying the probabilities for generating the quantiles of prob on the logit scale; these are used for the knot locations defining the spline whenever method = "ns". The default corresponds to a good choice based on four knots; see Harrel (2015, pp. 26-28) for details.
x	An object of class "calibrate".
...	Additional optional argument to be passed on to other methods.
refline.col	The color to use for the reference line. Default is "red".
refline.lty	The type of line to use for the reference line. Default is "dashed".
refline.lwd	The width of the reference line. Default is 1.

Value

A "calibrate" object, which is essentially a list with the following components:

"probs"

A data frame containing two columns: original (the original probability estimates) and calibrated (the calibrated probability estimates).

"calibrater"

The calibration function (essentially a fitted model object) which can be used to calibrate new probabilities.

"bs"

The Brier score between prob and y.

References

Harrell, Frank. (2015). Regression Modeling Strategies. Springer Series in Statistics. Springer International Publishing.

bgreenwell/calibrater documentation built on Dec. 31, 2020, 8:53 p.m.