Metadata-Version: 2.2
Name: dte_adj
Version: 0.1.4
Summary: This is a Python library for a research paper 'Estimating Distributional Treatment Effects in Randomized Experiments: Machine Learning for Variance Reduction'
License: MIT License
        
        Copyright (c) 2024 CyberAgent AI Lab
        
        Permission is hereby granted, free of charge, to any person obtaining a copy
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Project-URL: homepage, https://github.com/CyberAgentAILab/python-dte-adjustment
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.10
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: numpy~=1.26
Requires-Dist: matplotlib~=3.7
Requires-Dist: scipy~=1.13.1

## Overview

`dte_adj` is a Python package for estimating distribution treatment effects. It provides APIs for conducting regression adjustment to estimate precise distribution functions as well as convenient utils. For the details of this package, see [the documentation](https://cyberagentailab.github.io/python-dte-adjustment/).

## Installation

1. **Install from PyPI**
    ```sh
    pip install dte_adj
    ```

2. **Install from Source**

    ```sh
    git clone https://github.com/CyberAgentAILab/python-dte-adjustment
    cd python-dte-adjustment
    pip install -e .
    ```

## Basic Usage
Examples of how to use this package are available in [this Get-started Guide](https://cyberagentailab.github.io/python-dte-adjustment/get_started.html).

## Development
We welcome contributions to the project! Please review our [Contribution Guide](CONTRIBUTING.md) for details on how to get started.

## License

This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.

## Maintainers
- [Tomu Hirata](https://github.com/TomeHirata)
