v1.2026.3 improved sampling - #132
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Improved the sampling of all models by increasing the level of vectorization. These changes are all internal to the Stan models and are only visible to a user that is/has created a customized version of one of the models. In many cases, these improvements reduce the time required to run a model by 33%. Yay!
Added an argument to
prepare_model(predict_counts = TRUE)that allows the user to decrease the size of the stored model file (by ~10%) by removing the count-level predictions (ifpredict_counts = FALSE). Default is TRUE to include the predictions so that posterior and prior predictions still work by default.Added a scaling factor to the spatial models to ensure consistent interpretation of the priors for the spatial variance across any spatial graph. Following recommendations in Freni-Sterrantino et al. 2018. This is also largely an internal change, although the new realised variance term is accessible in the parameter summary as sdstrata_scaled and sdbeta_scaled.
Added some backend data to support better spatial overlay of the route locations and the strata maps. This is a partial patch in anticipation of the release of official route-path data from both national offices (expected within the 2026 calendar year and before the next annual data release). These changes are all internal and only relevant when
stratify( use_map = TRUE).