## Fitting your model is only the beginning: Bayesian posterior probability checks with rvars

Say we’ve collected data and estimated parameters of a model that give structure to the data. An important question to ask is whether the model is a reasonable approximation of the true underlying data generating process. If we did a good job, we should be able to turn around and generate data from the model itself that looks similar to the data we started with. And if we didn’t do such a great job, the newly generated data will diverge from the original.
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