DecoR: Deconfounding Time Series with Robust Regression
-
Updated
Jun 12, 2024 - Jupyter Notebook
DecoR: Deconfounding Time Series with Robust Regression
functions to estimate the Conditional Average Treatment Effects (CATE) and Population Average Treatment Effects on the Treated (PATT)
R Package for Simultaneous Multi-Bias Analysis
Qini curves for multi-armed treatment rules
Python Library for learning (Structure and Parameter), inference (Probabilistic and Causal), and simulations in Bayesian Networks.
An R package for causal sensitivity analysis methods
DoWhy is a Python library for causal inference that supports explicit modeling and testing of causal assumptions. DoWhy is based on a unified language for causal inference, combining causal graphical models and potential outcomes frameworks.
Lab Sessions - Causal Data Science for Business Analytics (Summer Term 2024)
This repository is a mirror. If you want to raise an issue or contact us, we encourage you to do it on Gitlab (https://gitlab.com/agrumery/aGrUM).
A large pile of interesting and/or useful information
Fast and customizable framework for automatic and quick Causal Inference in Python
Target: library for targeted inference https://targetlib.org/
DoubleML - Double Machine Learning in Python
Generalized Random Forests
Taking causal inference to the extreme!
causalimages: An R package for performing causal inference with image and image sequence data
causal-jobs is a project dedicated to revealing the status of causal inference in the European job market.
📦 Non-parametric Causal Effects Based on Modified Treatment Policies 🔮
An optimization algorithm to estimate the causal effects and produce distributionally robust prediction. It leverages the invariance property of causal mechanism over multiple environments.
Python Causal Impact Implementation Based on Google's R Package. Built using TensorFlow Probability.
Add a description, image, and links to the causal-inference topic page so that developers can more easily learn about it.
To associate your repository with the causal-inference topic, visit your repo's landing page and select "manage topics."