The Living Thing / Notebooks :

Bayesian model selection

Frequentist model selection is presumably not the only type. But what is model selection in a Bayesian context? Surely you don’t ever get some models with zero posterior proability? I thought we just kept all the models and weighted by posterior likelihood when making predictions? I still might wish to discard some models for reasons of computational tractability or what-have-you? What price do I pay for what sounds like unorthodoxy by the standards of my Intro-to-Bayes class?

TBD.

Interesting special case: Bayesian sparsity.

Cross-validation and Bayes

There is a relation between cross-validation and Bayes evidence, a.k.a. marginal likelihood - see FoHo19.

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