The brms documentation states that posterior_epred.brmsfit() returns “Expected Values of the Posterior Predictive Distribution.” My understanding is that this means for the model y \sim \alpha + \beta X + \epsilon, it would return the posterior for \alpha + \beta X for a given X for which to predic…

I guess Mcelreath can explain that a lot better than I can ( Statistical Rethinking 2022 Lecture 02 - Bayesian Inference - YouTube ) or chapter 3 in rethinking. For posterior predict you draw a random sample from the respective rng of the likelihood based on the parameter samples in your posterior. …

Expected Value of Posterior vs. Posterior of Expected Value with epred

Interfaces brms

JimBob August 11, 2022, 9:15am 3

@scholz is it broadly accurate to say that with posterior epred, each draw represents an average response, whereas for posterior_predict each draw is more like a randomly drawn individual response?

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Expected Value of Posterior vs. Posterior of Expected Value with epred

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