Metadata-Version: 2.1
Name: targeted
Version: 0.0.28
Summary: Python package for targeted inference.
Home-page: https://targetlib.org/python/
Author: Klaus Kähler Holst
Author-email: klaus.holst@maersk.com
License: Apache Software License
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: C++
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Scientific/Engineering :: Mathematics
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Operating System :: OS Independent
Description-Content-Type: text/markdown
Requires-Dist: pandas
Requires-Dist: scipy (>=1.3.2)
Requires-Dist: statsmodels (>=0.10.2)
Requires-Dist: patsy (>=0.5)
Requires-Dist: numpy (>=1.15)

# Targeted Learning Library

Python package for targeted inference.

**targeted** provides a number of methods for semi-parametric
estimation.  The library also contains implementations of various
parametric models (including different discrete choice models) and
model diagnostics tools.

The implemention currently includes
- **Risk regression models** with binary exposure
  (Richardson et al., 2017, doi:10.1080/01621459.2016.1192546)
- **Augmented Inverse Probability Weighted** estimators for missing
  data and causal inference (Bang and Robins, 2005,
  doi:10.1111/j.1541-0420.2005.00377.x)
- Model diagnostics based on **cumulative residuals** methods
- Efficient weighted **Pooled Adjacent Violator Algorithms**
- **Nested multinomial logit** models

Documentation and tutorials can be found at https://targetlib.org/python/.


