Metadata-Version: 2.1
Name: dvm
Version: 1.0.0
Summary: The Discrete Voter Model for ecological inference.
Home-page: https://github.com/hangulu/dvm
Author: Hakeem Angulu
Author-email: hakeem.angulu@gmail.com
License: UNKNOWN
Keywords: voting,ecological inference,gerrymandering
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.7
Description-Content-Type: text/markdown
Requires-Dist: numpy
Requires-Dist: pymc3
Requires-Dist: pandas
Requires-Dist: tqdm
Requires-Dist: tensorflow-probability
Requires-Dist: tensorflow
Requires-Dist: seaborn

## The Discrete Voter Model

The Discrete Voter Model is a method of ecological inference that grew out of [Hakeem Angulu's](https://github.com/hangulu) undergraduate [thesis](https://github.com/hangulu/thesis) for the departments of Computer Science and Statistics at Harvard College.

This new method of solving the ecological inference problem, using a mixture of contemporary statistical computing techniques, is implemented here. It can be used for multiple racial groups and candidates, and is shown to work well on randomly-generated mock election data.

The requirements can be installed with the included `Pipfile`. Go [here](https://realpython.com/pipenv-guide/) or [here](https://pipenv.kennethreitz.org/en/latest/) for more information on how to use `Pipenv`.


