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Roadmap
Tomás Capretto edited this page Oct 6, 2021
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30 revisions
Implement new families such as Beta and T and add usage examples #310, #311, #312-
Add a. We don't have the exact same thing, but there's a rich output when you print a model now..info()
or.describe()
method toModel
that prints model information similarily to print methods in R for model objects (example) Make getting started section executable #293Add a.predict()
method toModel
. We first need to update formulae so that any used transformation has memory about values used in the transformation (e.g.scale(x)
remembers the original mean an std values ofx
) #105- Save and load model. Not decided if they should be methods in
Model
or separated functions. #259
- Splines. This first requires to update formulae #214
- Gaussian processes. This may require to update formulae
- Revisit and expand tests in general
Decrease our dependency on statsmodels- Consolidate ArviZ integration
- Document new functionality
- Support new functionality (including loo-related diagnostics)
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Add/improve examples(this is always and ongoing effort, but we can say this has been achieved compared to the previous stage) Revisit default priors see #230- Work on porting code from books
- Regression and other stories
- Statistical Rethinking
- INLA support
- Allow "R-side" covariance structures and covariance priors in general (for varying effects too) #110
Bambi fails when p > n #278- Add example of posterior predictive sampling (and or check) #252
Add example of prior predictive sampling (and or check) #251