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Hierarchical Bayesian models specify priors on parameters and hyperpriors on the parameters of the prior distributions

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I'm working on a model with this basic structure: The square nodes are data, and the round nodes are parameters and/or latent variables. The left plate represents the "training observations" we actu …
asked Feb 26 by ShaunMcD