Graph-based multiple change-point detection

2021/10/04 by Yuxuan Zhang, Hao Chen, Zhang, Yuxuan +1 · 1 citation
Biochemistry, Genetics and Molecular Biology · #Gene Regulatory Network Analysis

paper · pdf · doi:10.48550/arxiv.2110.01170

Abstract

We propose a new multiple change-point detection framework for multivariate and non-Euclidean data. First, we combine graph-based statistics with wild binary segmentation or seeded binary segmentation to search for a pool of candidate change-points. We then prune the candidate change-points through a novel goodness-of-fit statistic. Numerical studies show that this new framework outperforms existing methods under a wide range of settings. The resulting change-points can further be arranged hierarchically based on the goodness-of-fit statistic. The new framework is illustrated on a Neuropixels recording of an awake mouse.

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