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 ...

Mixtures of normals provide a flexible model for estimating densities in a Bayesian framework. There are some difficulties with this model, however. First, standard reference priors yield improper ...

Bayesian techniques are widely used in these days for simultaneous estimation of several parameters in compound decision problems. Often, however, the main objective is to produce an ensemble of ...