Adding example on marginalizing models #628
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Love it! |
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It's missing the template stuff: https://www.pymc.io/projects/docs/en/latest/contributing/jupyter_style.html |
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What parts of the template are missing? Plot style and tags for the
notebook?
…On Sat, 20 Jan 2024, 03:58 Thomas Wiecki, ***@***.***> wrote:
It's missing the template stuff:
https://www.pymc.io/projects/docs/en/latest/contributing/jupyter_style.html
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There's more though, just read the whole page. |
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Waiting a few days in case someone else wants to review. |
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I want to! |
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But if you insist on using the NUTS sampler *exclusively*.
Link to wiki on Rao-Blackwell's theorem, and maybe only bring it up after explaining the advantages of marginalizing variables: more efficient sampling, unclear statistical properties of mixed sampling...
get a lower variance estimate of your parameters is a bit fuzzy. Get a smaller monte-carlo error on the estimates?
Call it pymc_experimental not pmx and maybe mention already the MarginalModel class with a cross-reference to the respective docs page
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What's the correct way to cross-reference the pymc_experimental docs?
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You can see how cross-references work in #614.
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None of the other histograms for the gmm have labels and title. What labels and title do you suggest?
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Ok hopefuly, that's more clear |
This adds an example for how to use the
MarginalModelclass inpymc-experimental📚 Documentation preview 📚: https://pymc-examples--628.org.readthedocs.build/en/628/