Alternatives and similar repositories for huber-causal-analysis

Users that are interested in huber-causal-analysis are comparing it to the libraries listed below

• nppackages / scpi
  Prediction and inference procedures for synthetic control methods with multiple treated units and staggered adoption.
  ☆37Updated 4 months ago
• keihirano / modern-sampling
  Course Materials for AEA Short Course on Modern Sampling Methods
  ☆29Updated 3 years ago
• MCKnaus / causalDML
  Implementation of Double Machine Learning
  ☆36Updated 6 months ago
• kwuthrich / scinference
  Inference for synthetic controls
  ☆39Updated 4 years ago
• QuantLet / Meta_learner-for-Causal-ML
  This repository provides R-code for the estimation of the conditional average treatment effect (CATE) using machine learning (ML) methods…
  ☆35Updated 9 months ago
• nlapier2 / PySensemakr
  Python implementation of the original R sensemakr package: https://github.com/carloscinelli/sensemakr
  ☆52Updated 5 months ago
• hmelberg / causal
  notebooks on methods for causal inference
  ☆36Updated last year
• FMenchetti / CausalMBSTS
  ☆16Updated 4 years ago
• NickCH-K / causaldata
  Packages of Example Data for The Effect
  ☆149Updated last year
• dballinari / Calibrating-doubly-robust-estimators-with-unbalanced-treatment-assignment
  Code to replicate the simulation study in the paper "Calibrating doubly-robust estimators with unbalanced treatment assignment"
  ☆14Updated last year
• joonho112 / Bayesian-causal-inference
  Tutorials on Stan for Bayesian causal inference
  ☆19Updated 4 months ago
• liulch / bpCausal
  A package for Bayesian causal inference with time-series cross-sectional data
  ☆26Updated last year
• bernardodionisi / differences
  difference-in-differences in Python
  ☆105Updated last year
• jgreathouse9 / FDIDTutorial
  This repository contains the Python code to estimate the Forward and Augmented DID estimators.
  ☆12Updated 11 months ago
• Mixtape-Sessions / Synthetic-Control-and-Clustering
  Synthetic-Control-and-Clustering taught by Alberto Abadie
  ☆56Updated 10 months ago
• py-econometrics / jaxonometrics
  Econometrics on the GPU (and CPU) via JAX
  ☆18Updated 4 months ago
• Larsvanderlaan / AdaptiveDML
  Adaptive debiased machine learning of treatment effects with the highly adaptive lasso
  ☆14Updated 8 months ago
• Mixtape-Sessions / Difference-in-Differences
  Difference-in-Differences
  ☆41Updated 3 years ago
• lihualei71 / cfcausal
  R package cfcausal
  ☆33Updated 2 years ago
• zalandoresearch / ACIC23-competition
  Data for and description of the ACIC 2023 data competition
  ☆32Updated 2 years ago
• swager / optrdd
  Optimized regression discontinuity designs
  ☆30Updated 2 years ago
• vsemenova / orthoml
  Code associated with paper: Orthogonal Machine Learning for Demand Estimation: High-Dimensional Causal Inference in Dynamic Panels, Seme…
  ☆27Updated 2 years ago
• carloscinelli / dml.sensemakr
  Sensitivity analysis tools for causal ML
  ☆18Updated 2 months ago
• Mixtape-Sessions / Empirical-Bayes
  Empirical Bayes Mixtape Session taught by Christopher Walters
  ☆17Updated 10 months ago
• d2cml-ai / 14.388_r
  This Jupyterbook has been created based on the tutorials of the course 14.388 Inference on Causal and Structural Parameters Using ML and …
  ☆14Updated 2 years ago
• sdfordham / pysyncon
  A python module for the synthetic control method
  ☆77Updated 6 months ago
• iamlemec / fastreg
  Fast sparse regressions with advanced formula syntax. OLS, GLM, Poisson, Maxlike, and more. High-dimensional fixed effects.
  ☆67Updated 2 years ago
• shoepaladin / causalinference_crashcourse
  Causal Inference Crash Course for Scientists - contains slides and Jupyter notebooks
  ☆107Updated 2 months ago
• MCKnaus / dmlmt
  Double Machine Learning for Multiple Treatments
  ☆41Updated 4 years ago
• gzervas / torchfe
  High-dimensional fixed effect estimation with pytorch
  ☆18Updated 4 years ago