Empirical Bayes is a statistical approach that combines Bayesian methods with empirical data to estimate prior distributions. This technique is particularly useful when prior knowledge is limited or uncertain, as it uses observed data to inform the prior distribution, making it more adaptable and reflective of reality. The method results in posterior distributions that incorporate both the prior estimates and the likelihood derived from the data, allowing for better inference in various applications.
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