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arXiv · 2504.21379

Non-parametric multiple change-point detection

Andreas Anastasiou·Piotr Fryzlewicz
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Abstract

We introduce a methodology, labelled Non-Parametric Isolate-Detect (NPID), for the consistent estimation of the number and locations of multiple change-points in a non-parametric setting. The method can handle general distributional changes and is based on an isolation technique preventing the consideration of intervals that contain more than one change-point, which enhances the estimation accuracy. As stopping rules, we propose both thresholding and the optimization of an information criterion. In the scenarios tested, which cover a broad range of change types, NPID outperforms the state of the art. An R implementation is provided.

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Andreas Anastasiou, Piotr Fryzlewicz. 2025-04-30. Non-parametric multiple change-point detection. https://arxiv.org/abs/2504.21379

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