AnaRitaNogueira / Methods-and-Tools-for-Causal-Discovery-and-Causal-InferenceLinks
This repository is used as a support for the paper "" (to be named)
☆25Updated 3 years ago
Alternatives and similar repositories for Methods-and-Tools-for-Causal-Discovery-and-Causal-Inference
Users that are interested in Methods-and-Tools-for-Causal-Discovery-and-Causal-Inference are comparing it to the libraries listed below
Sorting:
- Code to run submissions for the Atlantic Causal Inference Competition☆42Updated last year
- Python implementation of the original R sensemakr package: https://github.com/carloscinelli/sensemakr☆52Updated 3 months ago
- Tools for causal discovery in R☆19Updated 5 months ago
- Repository for Introduction to Bayesian Estimation of Causal Effects☆67Updated 4 years ago
- Demo data and code for "Sense and Sensitivity Analysis: Simple Post-Hoc Analysis of Bias Due to Unobserved Confounding".☆26Updated 3 years ago
- Package for heterogeneous causal effects in the presence of imperfect compliance (e.g., instrumental variables, fuzzy regression disconti…☆17Updated last year
- ☆96Updated last year
- Extensive tutorials for learning how to build deep learning models for causal inference (HTE) using selection on observables in Tensorflo…☆335Updated 10 months ago
- difference-in-differences in Python☆104Updated last year
- Packages of Example Data for The Effect☆143Updated 9 months ago
- Policy learning via doubly robust empirical welfare maximization over trees☆83Updated last month
- Replication files for Chernozhukov, Newey, Quintas-Martínez and Syrgkanis (2021) "RieszNet and ForestRiesz: Automatic Debiased Machine Le…☆14Updated 3 years ago
- Code for the paper "Joint Causal Inference from Multiple Contexts" (JMLR 2020)☆16Updated 5 years ago
- Distributional Random Forests (Cevid et al., 2020)☆44Updated 2 years ago
- Tutorial_Computational_Causal_Inference_Estimators☆37Updated 3 years ago
- Bayesian Causal Forests☆48Updated last year
- Gaussian dynamic Bayesian networks structure learning and inference based on the bnlearn package☆57Updated last year
- A collection of visual guides to help applied scientists learn causal inference.☆280Updated 2 years ago
- Sensitivity analysis tools for causal ML☆18Updated last month
- Dimension Reduction Methods for Multivariate Time Series☆61Updated 3 months ago
- Synthetic difference in differences for Python☆84Updated last year
- Implementation of Double Machine Learning☆36Updated 4 months ago
- Modelling extreme values☆15Updated last week
- R package for doubly robust estimates of causal effects in high-dimensions using flexible Bayesian methods☆26Updated 9 months ago
- Quasi-Oracle Estimation of Heterogeneous Treatment Effects☆114Updated 4 years ago
- ☆42Updated 4 years ago
- ☆44Updated 2 years ago
- A unified interface for the estimation of causal networks☆22Updated 5 years ago
- R implementation of Generic Machine Learning Inference (Chernozhukov, Demirer, Duflo and Fernández-Val, 2020).☆70Updated 7 months ago
- Code associated with paper: Orthogonal Machine Learning for Demand Estimation: High-Dimensional Causal Inference in Dynamic Panels, Seme…☆25Updated 2 years ago