syrgkanislab / orthogonal_regularized_estimation
Code associated with paper: Plug-in Regularized Estimation of High-Dimensional Parameters in Nonlinear Semiparametric Models, Chernozhukov, Nekipelov, Semenova, Syrgkanis, 2018
☆15Updated 4 years ago
Alternatives and similar repositories for orthogonal_regularized_estimation:
Users that are interested in orthogonal_regularized_estimation are comparing it to the libraries listed below
- Data for and description of the ACIC 2023 data competition☆32Updated last year
- Code associated with paper: Orthogonal Machine Learning for Demand Estimation: High-Dimensional Causal Inference in Dynamic Panels, Seme…☆24Updated last year
- Policy learning via doubly robust empirical welfare maximization over trees☆78Updated 8 months ago
- Fit Sparse Synthetic Control Models in Python☆80Updated 10 months ago
- ☆15Updated 7 months ago
- The cause2e package provides tools for performing an end-to-end causal analysis of your data. Developed by Daniel Grünbaum (@dg46).☆58Updated last year
- difference-in-differences in Python☆99Updated last year
- Packages of Example Data for The Effect☆135Updated 3 months ago
- An R package to estimate the effect of interventions on univariate time series using ARIMA models☆19Updated 9 months ago
- ☆16Updated 5 years ago
- A Python Package providing two algorithms, DAME and FLAME, for fast and interpretable treatment-control matches of categorical data☆56Updated 8 months ago
- Machine learning based causal inference/uplift in Python☆59Updated last year
- Code for Shopper, a probabilistic model of shopping baskets☆52Updated 4 years ago
- Python implementation of the original R sensemakr package: https://github.com/carloscinelli/sensemakr☆49Updated 2 months ago
- cem is a lightweight library for performing coarsened exact matching (CEM). CEM is a modern matching technique useful for causal inferenc…☆24Updated 8 months ago
- 💊 Comparing causality methods in a fair and just way.☆138Updated 4 years ago
- Time Series Forecasting and Imputation☆49Updated 3 years ago
- Implementation of algorithms from the paper "Globally-Consistent Rule-Based Summary-Explanations for Machine Learning Models: Application…☆24Updated 2 years ago
- The Identification and Estimation of Direct and Indirect Effects in A/B Tests through Causal Mediation Analysis☆23Updated 2 years ago
- Demo data and code for "Sense and Sensitivity Analysis: Simple Post-Hoc Analysis of Bias Due to Unobserved Confounding".☆27Updated 3 years ago
- Multiple Response Uplift (or heterogeneous treatment effects) package that builds and evaluates tradeoffs with multiple treatments and mu…☆66Updated 6 months ago
- ☆42Updated 3 years ago
- (ICML2020) “Counterfactual Cross-Validation: Stable Model Selection Procedure for Causal Inference Models’’☆31Updated last year
- Code for blog posts.☆19Updated last year
- Code for Conformal Counterfactual Inference under Hidden Confounding (KDD’24)☆10Updated 5 months ago
- Approximately balanced estimation of average treatment effects in high dimensions.☆34Updated 3 years ago
- Assessing Disparate Impacts of Personalized Interventions: Identifiability and Bounds☆11Updated 5 years ago
- GRAPL: A computational library for nonparametric structural causal modelling, analysis and inference☆80Updated 2 months ago
- A python module for the synthetic control method☆60Updated last month
- Notes and simulations on graduate level causal inference in statistics with applications to social sciences.☆23Updated 5 years ago