# Change-point detection for multivariate and non-Euclidean data with local dependency

@article{Chen2019ChangepointDF, title={Change-point detection for multivariate and non-Euclidean data with local dependency}, author={Hao Chen}, journal={arXiv: Methodology}, year={2019} }

In a sequence of multivariate observations or non-Euclidean data objects, such as networks, local dependence is common and could lead to false change-point discoveries. We propose a new way of permutation -- circular block permutation with a random starting point -- to address this problem. This permutation scheme is studied on a non-parametric change-point detection framework based on a similarity graph constructed on the observations, leading to a general framework for change-point detection…

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