Release 0.15.0

New features

• Add default priors for binomial and bernoulli families with logit link (#830)
• Add horseshoe prior (#836)
• Handle multivariate responses with HSGP (#856)

Maintenance and fixes

• Change the JAX random number generator key for 32 bit systems (#833)
• Change rename to replace in pre-render.py (#843)
• Fix out of sample prediction for multivariate families. It would not work for tables where the
  number of rows was different from the one used to fit the model (#847)
• Check variables before trying to access them in posterior predictive sampling (#851)
• Pass kwargs to nutpie + create env.yml file (#855)

Documentation

• Fix typos and incomplete doc strings (#765)
• Clarify elpd differences interepretation (#825)
• Fix the contributing readme link (#837)
• Add example using offset (#842)
• Fix model formula in negative binomial notebook (#859)
• Fix formatting in t-test examples (#861)
• Fix issue 812 Broken link (#862)
• Update repository documentation files (#865)

Release 0.14.0

New features

• Add configuration facilities to Bambi (#745)
• Interpet submodule now outputs informative messages when computing default values (#745)
• Bambi supports weighted responses (#761)
• Bambi supports constrained responses (#764)
• Implement compute_log_likelihood() method to compute the log likelihood on a model (#769)
• Add a class InferenceMethods that allows users to access the available inference methods and kwargs (#795)

Maintenance and fixes

• Fix bug in predictions with models using HSGP (#780)
• Fix get_model_covariates() utility function (#801)
• Use pm.compute_deterministics() to compute deterministics when bayeux based samplers are used (#803)
• Wrap all the parameters of the response distribution (the likelihood) with a pm.Deterministic (#804)
• Keep bayeux-ml as the single direct JAX-related dependency (#804)
• The response component only holds response information about the response, not about predictors of the parent parameter (#804)
• Resolve import error associated with bayeux (#822)

Documentation

• Our Code of Conduct now includes how to send a report (#783)
• Add polynomial regression example (#809)
• Add Contact form to our webpage (#816)

Deprecation

• f"{response_name}_obs" has been replaced by "__obs__" as the dimension name for the observation index (#804)
• f"{response_name}_{parameter_name}" is no longer the name for the name of parameters of the likelihood. Now Bambi uses "{parameter_name}" (#804)
• kind in Model.predict() now use "response_params" and "response" instead of "mean" and "pps" (#804)
• include_mean has been replaced by include_response_params in Model.fit() (#804)

Bambi 0.13.0

This is the first version of Bambi that is released with a Governance structure. Added in #709.
The highlights are the shiny interpret subpackage and the implementation of support for censored models.

New features

• Bambi now supports censored responses (#697)
• Implement "exponential" and "weibull" families (#697)
• Add "kidney" dataset (#697)
• Add interpret submodule (#684, #695, #699, #701, #732, #736)
  • Implements comparisons, predictions, slopes, plot_comparisons, plot_predictions, and plot_slopes
• Support censored families

Maintenance and fixes

• Replace univariate_ordered with ordered (#724)
• Add missing docstring for center_predictors (#726)
• Fix bugs in plot_comparison (#731)

Documentation

• Add docstrings to utility functions (#696)
• Migrate documentation to Quarto (#712)
• Add case study for MRP (#716)
• Add example about ordinal regression (#719)
• Add example about zero inflated models (#725)
• Add example about predictions for new groups (#734)

Deprecation

• Drop official suport for Python 3.8 (#720)
• Change plots submodule name to interpret (#705)

Bambi 0.12.0: Ordinal models and predictions on new groups

0.12.0

New features

• Implement new families "ordinal" and "sratio" for modeling of ordinal responses (#678)
• Allow families to implement a custom create_extra_pps_coord() (#688)
• Allow predictions on new groups (#693)

Maintenance and fixes

• Robustify how Bambi handles dims (#682)
• Fix links in FAQ (#686)
• Update additional dependencies install command (#689)
• Update predict pps docstring (#690)
• Add warning for aliases athat aren't used (#691)

Documentation

• Add families to the Getting Started guide (#683)

Bambi 0.11.0: The family grows

0.11.0

New features

• Add support for Gaussian Processes via the HSGP approximation (#632)
• Add new families: "zero_inflated_poisson", "zero_inflated_binomial", and "zero_inflated_negativebinomial" (#654)
• Add new families: "beta_binomial" and "dirichlet_multinomial" (#659)
• Allow plot_cap() to show predictions at the observation level (#668)
• Add new families: "hurdle_gamma", "hurdle_lognormal", "hurdle_negativebinomial", and "hurdle_poisson" (#676)

Maintenance and fixes

• Modify how HSGP is built in PyMC when there are groups (#661)
• Modify how Bambi is imported in the tests (#662)
• Prevent underscores from being removed in dim names (#664)
• Bump sphinx dependency to a version greater than 7 (#672)

Documentation

• Document how to use custom priors (#656)
• Fix name of arviz traceplot function in the docs (#666)
• Add example that shows how plot_cap() works (#670)

Bambi 0.10.0

New features

• Refactored the codebase to support distributional models (#607)
• Added a default method to handle posterior predictive sampling for custom families (#625)
• plot_cap() gains a new argument target that allows to plot different parameters of the response distribution (#627)

Maintenance and fixes

• Moved the tests directory to the root of the repository (#607)
• Don't pass dims to the response of the likelihood distribution anymore (#629)
• Remove requirements.txt and replace with pyproject.toml config file to distribute the package (#631)

Documentation

• Update examples to work with the new internals (#607)
• Fixed figure in the Sleepstudy example (#607)
• Add example using distributional models (#641)

Deprecation

• Removed versioned documentation webpage (#616)
• Removed correlated priors for group-specific terms (#607)
• Dictionary with tuple keys are not allowed for priors anymore (#607)

Bambi 0.9.3

Maintenance and fixes

• Update to PyMC >= 5, which means we use PyTensor instead of Aesara now (#613, #614)

Bambi 0.9.2

New features

• Implement censored() (#581)
• Add Formula class (#585)
• Add common numpy transforms to extra_namespace (#589)
• Add AsymmetricLaplace family for Quantile Regression (#591)
• Add 'transforms' argument to plot_cap() (#594)
• Add panel covariates to plot_cap() and make it more flexible (#596)

Maintenance and fixes

• Reimplemented predictions to make better usage of xarray data structures (#573)
• Keep 0 dimensional parameters as 0 dimensional instead of 1 dimensional (#575)
• Refactor terms for modularity and extensibility (#582)
• Remove seed argument from model.initial_point() (#592)
• Add build check function on prior predictive and plot prior (#605)

Documentation

• Add quantile regression example (#608)

Deprecation

• Remove automatic_priors argument from Model (#603)
• Remove string option for data input in Model (#604)

Bambi 0.9.1

Bambi 0.9.1

New features

• Add support for jax sampling via numpyro and blackjax samplers (#526)
• Add Laplace family (#524)
• Improve Laplace computation and integration (#555 and #563)

Maintenance and fixes

• Ensure order variable is preserved when ploting priors (#529)
• Treat offset accordingly (#534)
• Refactor tests to share data generation code (#531)

Documentation

• Update documentation following good inferencedata practices (#537)
• Add logos to repo and docs (#542)

Deprecation

• Deprecate method argument in favor of inference_method (#554)

Bambi 0.9.0

New features

• Bambi now uses PyMC 4.0 as it's backend. Most if not all your previous model should run the same, without the need of any change.
• Add Plot Conditional Adjusted Predictions plot_cap (#517)

Maintenance and fixes

• Group specific terms now work with numeric of multiple columns (#516)