SynthX: A Python Library for Advanced Synthetic Control Analysis
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Updated
May 3, 2024 - Python
SynthX: A Python Library for Advanced Synthetic Control Analysis
A curated list of awesome machine learning libraries for marketing, including media mix models, multi touch attribution, causal inference and more
This repository implements synthetic control methodology to estime the effect of active escape clauses on debt.
Synthetic difference in differences for Python
data repository for publicly available code and data of "Low-intensity fires mitigate the risk of catastrophic wildfires in California's forests"
A Penalized Synthetic Control Estimator for Disaggregated Data (JASA, 2021)
Tutorials for the synthetic control method for causal inference using PyMC
A Python package for causal inference using Synthetic Controls
Test code for disaggregated synthetic control with simulated data
Replication code for "RNN-based counterfactual prediction, with an application to homestead policy and public schooling"
Replication code for "State-Building through Public Land Disposal? An Application of Matrix Completion for Counterfactual Prediction"
Prediction and inference procedures for synthetic control methods with multiple treated units and staggered adoption.
A PyTorch implementation of the "robust" synthetic control model
Prevalence of Cannabis Use Disorder Post Legalization – Uruguay Case Study (Synthetic Control Method)
Factor-Based Imputation for Missing Data
Using the Synthetic Control method to effectively demonstrate the impact of Elon Musk purchasing Twitter on overall sentiment towards the company and on Twitter's stock price.
Using simulated data to understand synthetic control
A tool to run a pool of synthetic controls, conduct inference, and produce visualizations.
Comparative Case Studies using The Synthetic Control Method
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