---
title: Singular Bayesian Information Criterion
url: https://www.emergentmind.com/topics/singular-bayesian-information-criterion-sbic
type: topic
---

# Singular Bayesian Information Criterion

The Singular Bayesian Information Criterion (sBIC) generalizes the classical Bayesian Information Criterion (BIC) to statistical models exhibiting singularities, including non-identifiabilities, degenerate Fisher information, or latent variable structures. sBIC replaces the classical BIC penalty, which depends solely on the parametric dimension, with penalty terms arising from algebraic-geometric invariants that characterize the rate of concentration of the marginal likelihood in singular models. Its theoretical foundations rest on Watanabe's singular learning theory, which formalizes the asymptotic behavior of the Bayesian evidence for a wide class of non-regular, singular statistical models [1309.0911], [2402.12762].

##

Source: https://www.emergentmind.com/topics/singular-bayesian-information-criterion-sbic