Pylogit

==========================

Removed from package
--------------------

- Support for python2.7 or any python 3 version below 3.6. (67)


Bug fixes
---------

- Resolving import issues with the pylogit.bootstrap submodule. (27)
- Fixed flaky tests causing continuous integration build errors. (29)
- Fixed Hessian calculation so only the diagonal is penalized during ridge
regression. (33)


Improved Documentation
----------------------

- Made example notebooks py2 and py3 compatible. (28)


Trivial/Internal Changes
------------------------

- Included license file in source distribution. (18)
- Refactored the Hessian calculation to use less memory-intensive operations
based on linear-algebra decompositions. (30)
- Added journal reference for the accompanying paper in the project README.
(35)
- Added project logo to the repository. (46)
- Switched to pip-tools for specifying development dependencies. (58)
- Added Makefile to standardize development installation. (59)
- Switched to flit for packaging. (60)
- Added towncrier to repository. (61)
- Added tox to the repository for cross-version testing of PyLogit. (63)
- Added GitHub Actions workflow for Continuous Integration. (64)
- Converted the README.rst file to README.md. (65)
- Adding bump2version to development requirements. (66)

==========================

Bug fixes
---------

- Changed tqdm dependency to allow for anaconda compatibility.

==========================

Bug fixes
---------

- Added statsmodels and tqdm as package dependencies to fix errors with 0.2.0.

==========================

Added new features
------------------

- Added support for Python 3.4 - 3.6
- Added AIC and BIC to summary tables of all models.
- Added support for bootstrapping and calculation of bootstrap confidence intervals:

- percentile intervals,
- bias-corrected and accelerated (BCa) bootstrap confidence intervals, and
- approximate bootstrap confidence (ABC) intervals.

- Changed sparse matrix creation to enable estimation of larger datasets.


Trivial/Internal Changes
------------------------

- Refactored internal code organization and classes for estimation.

==========================

Added new features
------------------

- Added support to all logit-type models for parameter constraints during model estimation.
All models now support the use of the constrained_pos keyword argument.
- Added new argument checks to provide user-friendly error messages.
- Created more than 175 tests, bringing statement coverage to 99%.
- Updated the underflow and overflow protections to make use of L’Hopital’s rule where appropriate.


Bug fixes
---------

- Fixed bugs with the nested logit model.
In particular, the predict function, the BHHH approximation to the Fisher Information Matrix, and the ridge regression penalty in the log-likelihood, gradient, and hessian functions have been fixed.


Improved Documentation
----------------------

- Added new example notebooks demonstrating prediction, mixed logit, and converting long-format datasets to wide-format.
- Edited docstrings for clarity throughout the library.


Trivial/Internal Changes
------------------------

- Extensively refactored codebase.

==========================

Improved Documentation
----------------------
- Added python notebook examples demonstrating how to estimate the asymmetric choice models and the nested logit model.
- Corrected the docstrings in various places.
- Added new datasets to the github repo.