Different default priors for HSGP TVPs about pymc-marketing HOT 3 OPEN

This is awesome! Our users are definitively not experts in GPs; having suitable default priors is key 🙏! I'll take a look into the PR this week!

Thanks for bringing your expertise to the package 🙌

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Sure thanks @juanitorduz, the PR is quite bad, so forgive me on that. In my mind the first step is, does this proposal sound good? and then step 2 is how to implement it. The PR, mostly the notebook, is more to demonstrate that this works alright.

Also tagging @ulfaslak since this got kickstarted by a discussion we had.

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@bwengals I really like the proposal, and from my side, it is a key addition to the model! I especially like how the out-of-sample -prediction looks in the notebook. 💪

I suggest we work on step (2). One thing we need to keep in mind is what the default parameters should be when the optimization step in the find-constrained-prior fails. We can have a simple heuristic.

Please let me know how we can support you (besides the reviews) to work on the PR.

@wd60622 @ulfaslak any other thoughts from your side?

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