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Model comparison missing section #14
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i think we should use this section to explain how to handle multiple observations and ic calculation for hierarchical models (i.e. similarly to these two discourse answers: one, two). ArviZ docs on Does the rugby model sound as a good example for this? I don't like that leave one match out is so similar to leave half match/goal recording out. A couple options are to use football league data (premier or spanish league have 20 teams instead of 8, but still not sure would work) or using a similar model but on some other field where the equivalent to match has 3 or 4 components instead of only 2. |
Good idea! |
It is easy to copy from wikipedia 😉 and do some pandas magic. |
I support everything said here |
We should also include an explanation on the different methods of computing model's weights (mostly stacking vs pseudo-BMA) and more important the effects this have on the expected results. See arviz-devs/arviz#2077 for a common misconception we need to address |
plot_compare, WAIC. Bayes Factor
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