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Create methods for simulating from prior and predictive distributions #202

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damonbayer opened this issue Jun 18, 2024 · 1 comment · Fixed by #218
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Create methods for simulating from prior and predictive distributions #202

damonbayer opened this issue Jun 18, 2024 · 1 comment · Fixed by #218
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Pre-requisite to #169.

Model class should have model.sample_prior() and model.predict(samples) methods.
@damonbayer damonbayer added this to the 🐺 Lycorhinus milestone Jun 18, 2024
@damonbayer damonbayer self-assigned this Jun 18, 2024
This was referenced Jun 18, 2024
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@damonbayer damonbayer modified the milestones: 🐺 Lycorhinus, M Sprint Jun 21, 2024
@damonbayer damonbayer mentioned this issue Jun 26, 2024
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This was mentioned in Teams.

Did you have an (eventual) solution in mind beyond kwargs? I feel it works well for what we have now but might change in the future if there is something better.

Response:

It would be nice if you didn’t have to pass any arguments at all. I would want to somehow differentiate between a model and a model with data.

@damonbayer damonbayer changed the title Create and demonstrate methods for simulating from prior and computing predictive distributions Create methods for simulating from prior and predictive distributions Jul 1, 2024
@damonbayer damonbayer mentioned this issue Jul 1, 2024
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Create methods for simulating from prior and computing predictive distributions CDCgov/PyRenew
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