Jeffreys prior is a non-informative prior distribution used in Bayesian statistics, specifically designed to be invariant under reparameterization. It is derived from the Fisher information and aims to reflect a state of minimal prior knowledge about a parameter, making it particularly useful in situations where no specific prior information is available.
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