# R-squared for Bayesian Regression Models

“R-squared for Bayesian Regression Models” (2018), by Andrew Gelman et al. Mathematics research paper. Original abstract below, unchanged. No free PDF was found.

- Authors: Andrew Gelman, Ben Goodrich, Jonah Gabry, Aki Vehtari
- Published: December 10, 2018
- Field: Mathematics
- DOI: https://doi.org/10.1080/00031305.2018.1549100
- Source: https://aaltodoc.aalto.fi/handle/123456789/38878

## Abstract

The usual definition of R2 (variance of the predicted values divided by the variance of the data) has a problem for Bayesian fits, as the numerator can be larger than the denominator. We propose an alternative definition similar to one that has appeared in the survival analysis literature: the variance of the predicted values divided by the variance of predicted values plus the expected variance of the errors.

Canonical page: https://nerdi.pages.dev/paper/W2904925972
Read three real papers a day in Nerdi (iPhone): https://apps.apple.com/app/apple-store/id6813826387?pt=128757794&ct=web-paper&mt=8