AWhat changed
Schwarz derived a dimension-dependent log-sample penalty for asymptotic Bayesian model comparison in regular finite-dimensional settings, giving the criterion now called BIC.
Scientific scope
Schwarz derived a dimension-dependent log-sample penalty for asymptotic Bayesian model comparison in regular finite-dimensional settings, giving the criterion now called BIC. The model-selection penalty is an asymptotic approximation under the stated finite-dimensional regular model and prior assumptions. It is not an exact finite-sample evidence value or a universal rule for singular, high-dimensional or misspecified models. Prior and parameter-count conventions matter. Later generalized criteria retain separate credit.
Evidence
Source-linked, scoped account of the original work. The published scope states the scientific assumptions and remaining verification limits. WRS has not independently certified the full proof, experimental result or system benchmark.
Contributors
- Gideon Schwarz · SCIENCE: Original source-listed scientific author of this scoped work; byline does not determine effort fractions.
- Gideon Schwarz, Estimating the Dimension of a Model, original Annals paper, CMU copy
- IMS Crossref deposit for Schwarz 1978 dimension-estimation paper
Provisional WRS assessment, edition 2026-10-16.1. Independent expert calibration is pending. This grade does not certify correctness or assign ownership.
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