Bambi 0.8.0

Bambi 0.8.0

New features

• Add VonMises ("vonmises") built-in family (#453)
• Model.predict() gains a new argument include_group_specific to determine if group-specific effects are considered when making predictions (#470)
• Add Multinomial ("multinomial") built-in family (#490)

Maintenance and fixes

• Add posterior predictive sampling method to "categorical" family (#458)
• Require Python >= 3.7.2 to fix NoReturn type bug in Python (#463)
• Fixed the wrong builtin link given by link="inverse" was wrong. It returned the same result as link="cloglog" (#472)
• Replaced plain dictionaries with namedtuples when same dictionary structure was repeated many times (#472)
• The function check_full_rank() in utils.py now checks the array is 2 dimensional (#472)
• Removed _extract_family_prior() from bambi/families as it was unnecesary (#472)
• Removed bambi/families/utils.py as it was unnecessary (#472)
• Removed external links and unused datasets (#483)
• Replaced "_coord_group_factor" with "__factor_dim" and "_coord_group_expr" with "__expr_dim" in dimension/coord names (#499)
• Fixed a bug related to modifying the types of the columns in the original data frame (#502)

Documentation

• Add circular regression example (#465)
• Add Categorical regression example (#457)
• Add Beta regression example (#442)
• Add Radon Example (#440)
• Fix typos and clear up writing in some docs (#462)
• Documented the module bambi/defaults (#472)
• Improved documentation and made it more consistent (#472)
• Cleaned Strack RRR example (#479)

Deprecation

• Removed old default priors (#474)
• Removed draws parameter from Model.predict() method (#504)

Bambi 0.7.1

This is a patch release where we fix a bug related to the shape of 2 level categorical group-specific effects (#441)

Bambi 0.7.0

This release includes a mix of new features, fixes, and new examples on our webpage.

New features

• Add "categorical" built-in family (#426)
• Add include_mean argument to the method Model.fit() (#434)
• Add .set_alias() method to Model (#435)

Maintenance and fixes

• Codebase for the PyMC backend has been refactored (#408)
• Fix examples that averaged posterior values across chains (#429)
• Fix issue #427 with automatic priors for the intercept term (#430)

Documentation

• Add StudentT regression example, thanks to @tjburch (#414)
• Add B-Spline regression example with cherry blossoms dataset (#416)
• Add hirarchical linear regression example with sleepstudy dataset (#424)

Bambi 0.6.3

Use formulae 0.2.0

Bambi 0.6.2

Minor fixes to code and docs

Bambi 0.6.1

Mainly changes to the docs and minor fixes.

Bambi 0.6.0

Many changes are included in this release. Some of the most important changes are

• New model families (StudentT, Binomial, Beta).
• In-sample and out-of-sample predictions.
• Improved sampling performance due to predictor centering when the model contains an intercept.
• New default priors (similar to rstanarm default priors).
• It's possible to use potentials.
• There's a new function to load datasets used throughout examples

Bambi 0.5.0

The main changes in this release can be summarized as follows

• Modified the API. Now all information relative to the model is passed in Model instantiation instead of in Model.fit().
• Fixed Gamma, Wald, and Negative Binomial families.
• Changed theme of the webpage and now the documentation is built automatically.

Release 0.4.1

The aim of this release is to update to formulae 0.0.9, which contains several bug fixes. There are also other minor fixes and improvements that can be found in the changelog.

The formulae bambino

The main change in this release is the use of formulae, instead of patsy, to parse model formulas.