arXiv:2609.36594v1 Announce Type: cross
Abstract: We study multiple change-point detection in multivariate time series whose distributions change in a piecewise constant manner. Distributional change...
By Xiaokai Luo, Chenghao Xu, Haotian Xu, Carlos Misael Madrid Padilla, Daren Wang
skchange is an open‑source Python library that provides fast and flexible algorithms for detecting structural changes in time series. It offers modular, composable methods based on cost minimisation and statistical tests, and includes features such as anomalous segment detection, high‑dimensional data support, automatic penalty calibration, and a wide range of built‑in costs and tests. The library follows scikit‑learn conventions and uses Numba for high computational performance, with source code and documentation available on GitHub.
arXiv:2608. 19767v1 Announce Type: cross Abstract: Skchange is an open-source Python library for detecting structural changes in time series.
By Martin Tveten, Johannes Voll Kolst{\o}, Per August Jarval Moen
The paper introduces a sequential change‑point detection method for time‑ordered data where neither the pre‑ nor post‑change distributions have closed forms. It trains a conditional diffusion model on pre‑change data, uses its probability flow ODE to map observations to a Gaussian latent space, and then applies the Maximum Mean Discrepancy as a test statistic. The authors derive closed‑form components under the Gaussian null, establish the statistic’s asymptotic distribution as a degenerate U‑statistic, and implement an online Shiryaev–Roberts procedure with exact threshold calibration to detect arbitrary distributional shifts without parametric assumptions.
By Artem Kraevskiy, Artem Prokhorov
arXiv:2512. 07541v3 Announce Type: replace-cross Abstract: Inspired by graph-based methodologies, we introduce a novel graph-spanning algorithm designed to identify changes in both offline and online data across low to high dimensions.
By Katerina Papagiannouli, Yang-wen Sun, Vladimir Spokoiny
arXiv:2605. 30363v2 Announce Type: replace-cross Abstract: Regime shifts in financial markets reorganise the joint dynamics of asset prices and macro variables, breaking any single-regime calibration.
By Mingxuan Yi, Vidal Mehra, Jing Chen, John Cartlidge