Bayesian estimation methods form a dynamic branch of statistical inference, utilising Bayes’ theorem to update probabilities in light of new evidence. This framework combines prior knowledge with ...
In the ever-evolving toolkit of statistical analysis techniques, Bayesian statistics has emerged as a popular and powerful methodology for making decisions from data in the applied sciences. Bayesian ...
The parametric bootstrap can be used for the efficient computation of Bayes posterior distributions. Importance sampling formulas take on an easy form relating to the deviance in exponential families ...
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