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| Main Authors: | , |
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| Format: | Preprint |
| Published: |
2023
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2311.11259 |
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| _version_ | 1866916426461216768 |
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| author | Krebs, Johannes Rademacher, Daniel |
| author_facet | Krebs, Johannes Rademacher, Daniel |
| contents | In this paper, we study the stability of commonly used filtration functions in topological data analysis under small perturbations of the underlying nonrandom point cloud. Relying on these stability results, we then develop a test procedure to detect and determine structural breaks in a sequence of topological data objects obtained from weakly dependent data. The proposed method applies for instance to statistics of persistence diagrams of $\mathbb{R}^d$-valued Bernoulli shift systems under the Čech or Vietoris-Rips filtration. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2311_11259 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | On the stability of filtration functions for dependent data with applications to break detection Krebs, Johannes Rademacher, Daniel Statistics Theory In this paper, we study the stability of commonly used filtration functions in topological data analysis under small perturbations of the underlying nonrandom point cloud. Relying on these stability results, we then develop a test procedure to detect and determine structural breaks in a sequence of topological data objects obtained from weakly dependent data. The proposed method applies for instance to statistics of persistence diagrams of $\mathbb{R}^d$-valued Bernoulli shift systems under the Čech or Vietoris-Rips filtration. |
| title | On the stability of filtration functions for dependent data with applications to break detection |
| topic | Statistics Theory |
| url | https://arxiv.org/abs/2311.11259 |