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Roadmap
Osvaldo Martin edited this page Oct 5, 2021
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Implement new families such as Beta and T and add usage examples #310, #311, #312- Add a
.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 #215
- ...
- Revisit and expand tests in general
- Decrease our dependency on statsmodels
- Consolidate ArviZ integration
- Document new functionality
- Support new functionality (including loo-related diagnostics)
- Add/improve examples
- 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