Bayesian estimation is a statistical method that incorporates prior beliefs or information along with current evidence to update the probability of a hypothesis. This technique uses Bayes' theorem to combine prior distributions with likelihood functions, producing a posterior distribution that reflects the updated beliefs about the parameters being estimated. It is particularly useful in situations where data is limited or uncertain, as it allows for the incorporation of subjective prior knowledge into the analysis.
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