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What is a prior predictive check?

hard

Answer

  • Simulate data from the prior alone: θ ~ p(θ), y ~ p(y    θ)p(y\; \mid \;{\theta}).
  • Check whether generated y is plausible given domain knowledge (e.g. simulated coin flip probabilities in [0, 1]; simulated log-revenues aren't in the trillions).
  • Catches absurd priors before running expensive inference.
  • Modern Bayesian workflow (Gelman et al.): prior predictive → fit → posterior predictive → repeat.
  • Essential in real modeling.
Check yourself — multiple choice
  • Random
  • Simulate y from prior alone; check plausibility against domain knowledge; catches absurd priors before expensive inference
  • Same as posterior predictive
  • Not needed

Prior predictive check: simulate from prior; verify plausibility.

#bayesian

Practise Statistics Fundamentals

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