# BRcal: An R Package to Boldness-Recalibrate Probability Predictions

arXiv: https://arxiv.org/abs/2409.13858 · HTML: https://mlsanity.com/paper/2409.13858/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 20 Sep 2024.

## Built on by (most cited first, 1 of 1)

- [Monitoring the calibration of probability forecasts with an application to concept drift detection involving image classification](https://mlsanity.com/paper/2510.25573/) (2025)

## Abstract (arXiv)

When probability predictions are too cautious for decision making, boldness-recalibration enables responsible emboldening while maintaining the probability of calibration required by the user. We formulate boldness-recalibration as a nonlinear optimization of boldness with a nonlinear inequality constraint on calibration. We further show that recalibration based on the maximized linear log odds likelihood also maximizes the posterior probability of calibration. We introduce BRcal, an R package implementing boldness-recalibration and supporting methodology as recently proposed. The BRcal package provides direct control of the calibration-boldness tradeoff and visualizes how different calibration levels change individual predictions. We present a new real world case study involving housing foreclosure predictions. The BRcal package is available on the Comprehensive R Archive Network (CRAN) (https://cran.r-project.org/web/packages/BRcal/index.html) and on Github (https://github.com/apguthrie/BRcal).