3 papers
stat.ME2026
focus and focus-cpt: Fast Online Changepoint Detection in R and Python
Gaetano Romano, Kes Ward, Yuntang Fan +4
We present an R and Python package for fast online changepoint detection in univariate and multivariate data streams for a variety of models. The package implements the focus famil…
stat.ME2026
An Efficient Likelihood Ratio Test for Online Changepoint Detection in the Presence of Autocorrelation
Yuntang Fan, Paul Fearnhead, Idris A. Eckley +1
Changepoint detection methods have seen considerable development in recent years, with online algorithms capable of identifying structural changes in streaming data in near real ti…
stat.ME2026
Exact Multiple Change-Point Detection Via Smallest Valid Partitioning
Vincent Runge, Anica Kostic, Alexandre Combeau +1
We introduce smallest valid partitioning (SVP), a segmentation method for multiple change-point detection in time-series. SVP relies on a local notion of segment validity: a candid…