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Bayesian inference is a method of statistical inference that relies on treating the model parameters as random variables and applying Bayes' theorem to deduce subjective probability statements about the parameters or hypotheses, conditional on the observed dataset.
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Comparing maximum likelihood estimation (MLE) and Bayes' Theorem
From STAN reference manual:
If the prior is uniform, the posterior mode corresponds to the
maximum likelihood estimate (MLE) of the parameters. If the prior is
not uniform, the posterior mode …