Metadata-Version: 2.1
Name: firthlogist
Version: 0.0.4
Summary: Python implementation of Logistic Regression with Firth's bias reduction
Home-page: https://github.com/jzluo/firthlogist
License: MIT
Author: Jon Luo
Author-email: jzluo@alumni.cmu.edu
Requires-Python: >=3.9,<3.11
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.9
Classifier: Topic :: Scientific/Engineering
Requires-Dist: numpy (>=1.22.4,<2.0.0)
Requires-Dist: pandas (>=1.4.2,<2.0.0)
Requires-Dist: pytest (>=7.1.2,<8.0.0)
Requires-Dist: scikit-learn (>=1.1.1,<2.0.0)
Project-URL: Repository, https://github.com/jzluo/firthlogist
Description-Content-Type: text/markdown

# firthlogist

[![PyPI](https://img.shields.io/pypi/v/firthlogist.svg)](https://pypi.org/project/firthlogist/)

A Python implementation of Logistic Regression with Firth's bias reduction.

WIP!

## Installation
    pip install firthlogist

## Usage
firthlogist follows the sklearn API.

```python
from firthlogist import FirthLogisticRegression
firth = FirthLogisticRegression()
firth.fit(X, y)
coefs = firth.coef_
```

## References
Firth, D (1993). Bias reduction of maximum likelihood estimates.
*Biometrika* 80, 27–38.

Heinze G, Schemper M (2002). A solution to the problem of separation in logistic
regression. *Statistics in Medicine* 21: 2409-2419.

