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Closing this discussion, as there is a new Plot class that includes prior_predictive, replacing the older plot_prior_predictive. |
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I’m working with the multidimensional MMM implementation (pymc_marketing/mmm/multidimensional.py) and I’m trying to replicate the same workflow I use with the “standard” MMM class (pymc_marketing/mmm/mmm.py) for plotting prior predictive.
With the MMM class in mmm.py, I’m able to generate and plot prior predictive checks (e.g., via the model’s prior predictive sampling / helper methods, then plotting the resulting draws over time). However, with the multidimensional MMM object I’m not sure what the intended pattern is, or which helper method(s) to use.
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