Bayesian Change-Point Detection and Time Series Decomposition

Taking causal inference to the extreme!

Causal Inference Using Quasi-Experimental Methods

Interrupted time series and synthetic control methodology for epidemiological criminology

Economics notes and R code covering microeconomics, macroeconomics, regression, time series, and policy analysis

​A tutorial on interrupted time series regression for the evaluation of public health interventions

Two-stage interrupted time series analysis of excess mortality in Italy during the COVID-19 pandemic

Time series analysis of Sheffield's Clean Air Zone effectiveness: ARIMA forecasting, Prophet modeling, ITS regression. Proven 30-44% NO₂ reduction with statistical significance (p<0.001). Complete R pipeline with reproducible methodology.

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

Estimating pricing impact on churn using interrupted time series and model-based counterfactuals.

Computational pipeline for detecting Russian foreign-broadcast propaganda and its amplification of social cleavages in Cyprus. Features multilingual NLP (XLM-RoBERTa, BERTopic, stanza), multi-source scraping (Telegram, Twitter/X, RT, Sputnik), and interrupted time series analysis.

Do AI coding assistants change code quality? An ITS + DiD mining study over 272 treated / 299 control OSS repositories.

This is the repo for the statistical and machine learning analysis for the obesity surgery effects on asthma severity.