Théorème de Bernstein-von Mises

Définition

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Bernstein–Von Mises Theorem

The Bernstein–Von Mises theorem states that the more data available for sampling, the less influence the prior probability has on a prediction model, at least for common Bayesian inference models that have a specific set of constraints. As the data pool expands, the posterior distribution grows more independent of the prior probability assumption and the posterior’s curve looks just like (is asymptotic to) a sampling distribution drawn from a maximum likelihood estimator.

Source : DeepAI.org