causal-impact

CausalLift: Python package for causality-based Uplift Modeling in real-world business

A resource list for causality in statistics, data science and physics

Python tools for regression discontinuity designs

Causal Inference Using Quasi-Experimental Methods

Bayesian CausalImpact for Python — R-compatible Gibbs sampler in Rust (PyO3), 30x faster, no TensorFlow

Turn before/after time-series questions into counterfactual charts, reproducible reports, share packages, and AI-agent-ready handoffs.

Some examples of using bsts (Bayesian Structural Time Series) to build causal impact models

Claude Code skill for measuring causal impact of marketing campaigns using Bayesian structural time series

Daily CTA ridership forecasting (SARIMA, GARCH, Prophet, LSTM) with a Chow / SARIMAX / Bayesian Causal Impact analysis of COVID-19's permanent effect.

Quantifying the impact of a documentary on KeepCup search volume

Working with the causaleffects and igraph

Did that policy actually work? Causal inference for time series — ARIMA, Bayesian STS, Diff-in-Diff, Synthetic Control. Streamlit app with counterfactual charts and PDF reports.

Causal geo-experiment measuring incremental campaign lift with Bayesian structural time series (CausalImpact)

Quasi-experiment analytics platform: измерение причинного эффекта без A/B-теста (Diff-in-Diff, Event Study, Causal Impact, ITS, Forecast baseline, Anomaly Detection) — Streamlit + statsmodels

Evaluating the impact of Dieselgate and COVID-19 on German automotive stock volatility (Volkswagen, BMW, Mercedes-Benz) using CausalImpact (BSTS) and Synthetic Control for risk management.