recalibrate.p: Recalibrate posterior probabilities

In wevid: Quantifying Performance of a Binary Classifier Through Weight of Evidence

Description

Transforms posterior probabilities to logits, fits a logistic regression model and returns the predictive probabilities from this model.

Usage

recalibrate.p(y, posterior.p)

Arguments

y	Binary outcome label (0 for controls, 1 for cases).
posterior.p	Vector of posterior probabilities.

Value

Recalibrated posterior probabilities.

wevid documentation built on Sept. 12, 2019, 5:04 p.m.