https://github.com/timothyb0912/pylogit

A python package for estimating conditional logit models.
https://github.com/timothyb0912/pylogit

discrete-choice

Last synced: 3 months ago
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A python package for estimating conditional logit models.

• Host: GitHub
• URL: https://github.com/timothyb0912/pylogit
• Owner: timothyb0912
• License: bsd-3-clause
• Created: 2016-03-15T01:29:46.000Z (over 8 years ago)
• Default Branch: master
• Last Pushed: 2022-07-12T12:30:01.000Z (over 2 years ago)
• Last Synced: 2024-07-16T12:34:25.643Z (4 months ago)
• Topics: discrete-choice
• Language: Python
• Homepage: https://pypi.org/project/pylogit/
• Size: 2.78 MB
• Stars: 184
• Watchers: 14
• Forks: 103
• Open Issues: 29
• Metadata Files:
  • Readme: README.md
  • Changelog: CHANGELOG.rst
  • License: LICENSE.txt

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README

        
![PyLogit Logo](./images/PyLogit_Final-small-04.png)

![Tests](https://github.com/timothyb0912/pylogit/workflows/Testing/badge.svg)

# PyLogit

PyLogit is a Python package for performing maximum likelihood estimation of conditional logit models and similar discrete choice models.

## Main Features

- It supports

   - Conditional Logit (Type) Models

     - Multinomial Logit Models

     - Multinomial Asymmetric Models

        - Multinomial Clog-log Model

        - Multinomial Scobit Model

        - Multinomial Uneven Logit Model

        - Multinomial Asymmetric Logit Model

   - Nested Logit Models

   - Mixed Logit Models (with Normal mixing distributions)

- It supports datasets where the choice set differs across observations

- It supports model specifications where the coefficient for a given variable may be

   - completely alternative-specific   

   (i.e. one coefficient per alternative, subject to identification of the coefficients),

   - subset-specific  

   (i.e. one coefficient per subset of alternatives, where each alternative belongs to only one subset, and there are more than 1 but less than J subsets, where J is the maximum number of available alternatives in the dataset),

   - completely generic  

   (i.e. one coefficient across all alternatives).

## Installation

Available from [PyPi](https://pypi.python.org/pypi/pylogit):

```

pip install pylogit

```

Available through [Anaconda](https://anaconda.org/conda-forge/pylogit):

```

conda install -c conda-forge pylogit

```

or

```

conda install -c timothyb0912 pylogit

```

## Usage

For Jupyter notebooks filled with examples, see [examples](./examples/).

## For More Information

For more information about the asymmetric models that can be estimated with PyLogit, see the following paper

> Brathwaite, T., & Walker, J. L. (2018). Asymmetric, closed-form, finite-parameter models of multinomial choice. Journal of Choice Modelling, 29, 78–112. https://doi.org/10.1016/j.jocm.2018.01.002

A free and better formatted version is available at [ArXiv](http://arxiv.org/abs/1606.05900).

## Attribution

If PyLogit (or its constituent models) is useful in your research or work, please cite this package by citing the paper above.

## License

Modified BSD (3-clause). See [here](./LICENSE.txt).

## Changelog

See [here](./CHANGELOG.rst).