The existing time-varying parameters notebooks (Time-Varying Media, Time-Varying Parameters) show how to use the feature but don't explain why you'd choose it over other approaches to non-stationarity, such as likelihood tempering/weighting.
A documentation page (either standalone or as an expanded introduction to an existing TVP notebook) covering the conceptual distinction would be valuable: adjusting inference (reweighting the likelihood to favour recent data) vs modelling the changing data-generating process directly (time-varying parameters). This framing came up in an EAP advisory discussion where a production MMM team had implemented likelihood tempering and needed guidance on the tradeoffs.
[@drbenvincent suggested this]
The existing time-varying parameters notebooks (Time-Varying Media, Time-Varying Parameters) show how to use the feature but don't explain why you'd choose it over other approaches to non-stationarity, such as likelihood tempering/weighting.
A documentation page (either standalone or as an expanded introduction to an existing TVP notebook) covering the conceptual distinction would be valuable: adjusting inference (reweighting the likelihood to favour recent data) vs modelling the changing data-generating process directly (time-varying parameters). This framing came up in an EAP advisory discussion where a production MMM team had implemented likelihood tempering and needed guidance on the tradeoffs.
[@drbenvincent suggested this]