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@Dekermanjian Dekermanjian commented Aug 31, 2025

updated notebook to utilize the newly added sample_filter_outputs method.

Previously we were pulling out the filter outputs by passing save_kalman_filter_outputs_in_idata to the build_statespace method. This will be deprecated in the future and we have added a utility method sample_filter_outputs to allow users to sample the KF outputs.


📚 Documentation preview 📚: https://pymc-examples--804.org.readthedocs.build/en/804/

2. Improved 24-hour ahead forecasts of simplest model
3. Added a section and model with how to add exogenous variables to the model
2. cleaned up typos and figure sizes/zoom
2. Added a non-linear B-Splines section
2. Added closing remarks section
3. Updated references bib file
2. Restructured function docstrings to comply with numpy's guidestyle
3. Added ODE derivation of Newtonian equations of motion
4. Added legend to origins scatterplot
5. Fixed issue with passing in future covariates into exogenous model when forecasting
6. Added model evaluations and comparisons
7. Fixed issue with diffuse initialization of P0
2. updated generate forecast utility
3. updated how mode=JAX is specified
4. renamed simple model to Newtonian model
5. added explanations to exogenous data duplicating and mirroring
6. added note on how the newtonian model differs from typical parameteric models
…ans and covariances. Updated plotly setting to automatically select renderer
…state means and covariances. Updated plotly setting to automatically select renderer"

This reverts commit 07355d2.

Revert using conditional posterior to using save_kalman_filter_outputs_in_idata
… with A and sometimes with T to only being referred to using T
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