Hierarchical Bayesian inference

• Assume flexible population model
• Examples: Gaussian, Gaussian mixture, beta distribution
• Fold in posterior samples for object i
• Likelihood for population parameters - MCMC
• Importance sampling from posteriors
• need flat priors, see Buchner+17a for details

Product over objects

Mean over samples