Non-parametric method for estimating regime change in bivariate time series setting.

A new tool for detecting changes in dynamic rules in population time series data

A Smart Constitution Code and a Supporting Draft

Predictive modeling of 67 years of atmospheric CO₂ using regime‐shift detection (STL + PELT) and ensemble forecasting (ARIMA, SARIMA, Holt–Winters, RF, ANN, LSTM). Evaluated with in-sample, out-of-sample, and prequential rolling forecasts to deliver reliable five-year projections with regime shif

Bayesian Online Changepoint Detection for production metrics, a calibrated probability of regime change per observation, zero runtime dependencies, TypeScript with a node-free core

An honest empirical test of subjective/objective reconciliation for forecasting democratic backsliding using ensemble learning.