Metadata-Version: 2.1
Name: Debias-Infer
Version: 0.0.2
Summary: Efficient Inference on High-Dimensional Linear Models With Missing Outcomes
Home-page: https://github.com/zhangyk8/Debias-Infer
Author: Yikun Zhang
Author-email: yikunzhang@foxmail.com
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.8
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: numpy >=1.23
Requires-Dist: scipy >=1.1.0
Requires-Dist: cvxpy[cvxopt,mosek]
Requires-Dist: scikit-learn
Requires-Dist: statsmodels

[![PyPI pyversions](https://img.shields.io/pypi/pyversions/Debias-Infer.svg)](https://pypi.python.org/pypi/Debias-Infer/)
[![PyPI version](https://badge.fury.io/py/Debias-Infer.svg)](https://badge.fury.io/py/Debias-Infer)
[![Downloads](https://static.pepy.tech/badge/Debias-Infer)](https://pepy.tech/project/Debias-Infer)
[![Documentation Status](https://readthedocs.org/projects/sconce-scms/badge/?version=latest)](http://debias-infer.readthedocs.io/?badge=latest)

# Efficient Inference on High-Dimensional Linear Models With Missing Outcomes

This package implement the proposed debiasing method for conducting valid inference on the high-dimensional linear regression function with missing outcomes. We also document all the code for the simulations and real-applications in our paper [here](https://github.com/zhangyk8/Debias-Infer/tree/main/Paper_Code).
