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usage/predictive-distributions/index.qmd

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p(\tilde{x}) = \int p(\tilde{x} | \theta) p(\theta) d\theta,
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$$
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In exactly analogous fashion to above, you could sample from the prior distribution of the conditioned model, and _then_ pass that to `predict`:
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In an exactly analogous fashion to above, you could sample from the prior distribution of the conditioned model, and _then_ pass that to `predict`:
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```{julia}
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prior_params = sample(model, Prior(), 1_000; progress=false)

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