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Bernstein–von_Mises_theorem entered the ranking for the first time today at position #. This is its highest position ever recorded.
This topic has appeared in the English Wikipedia rankings 1 time. It first appeared on 2026-06-25 and was most recently seen on 2026-06-25.
In Bayesian inference, the Bernstein–von Mises theorem provides the basis for using Bayesian credible sets for confidence statements in parametric models. It states that under some conditions, a posterior distribution converges in total variation distance to a multivariate normal distribution centered at the maximum likelihood estimator with covariance matrix given by , where is the true population parameter and is the Fisher information matrix at the true population parameter value:
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