Spline showcase in Covid-19 ITS example

[milesalanmoore]

This PR updates the COVID interrupted time-series notebook to show a spline-based alternative to a simple linear baseline. It adds a more flexible specification, demonstrates the diagnostics needed to assess model fit and convergence, also demonstrates a custom RW2 prior and Bayesian P-spline approach that leverages pymc-extra's VariableFactory protocol and walks through the resulting counterfactual trend and estimated intervention effect. This addresses #475.

This is just a proof of concept / rough draft! I recognize the narrative still needs revision. For now: I wonder if something like this is what you had in mind for #475 @drbenvincent ?

Thank you for thoughtfully maintaining a great library!

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Documentation build overview

📚 causalpy | 🛠️ Build #34303465 | 📁 Comparing 98a98d0 against latest (994f665)

  🔍 Preview build  

2 files changed

± 404.html
± notebooks/interrupted-time-series-covid.html

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Codecov Report

✅ All modified and coverable lines are covered by tests.
✅ Project coverage is 96.03%. Comparing base (994f665) to head (517e574).

Additional details and impacted files

@@           Coverage Diff           @@
##             main    #1180   +/-   ##
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  Coverage   96.03%   96.03%           
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  Files         105      105           
  Lines       16363    16370    +7     
  Branches      916      916           
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+ Hits        15714    15721    +7     
  Misses        485      485           
  Partials      164      164           

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