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Roadmap
Add examples for the following cases:
- Offsets #418.
- Potentials#384. Don't forget to explain what is a potential and where the name comes from.
- Beta family #369.
- Categorical family #436.
- Posterior predictive check #252. I think we already use it in some places, but it is not advertised enough.
- Piecewise regression.
This formula object will allow us to pass multiple formulas for different components of the model. We take the distributional model term from brms (this vignette), which says:
[...] refer to a model, in which we can specify predictor terms for all parameters of the assumed response distribution.
In other words, we not only have predictors for the mean, but also predictors for other parameters such as the dispersion. For example, this enables heteroskedastic linear regression models.
The type of models just mentioned above.
It would be really nice if we could move forward with what it is in #365. At some point, we're going to face it. For example, if we allow distributional models and we use the same predictor for the mean and the standard deviation. How do we allow users to use different priors for each case?
- 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