Seeded intervals and noise level estimation in change point detection: A discussion of Fryzlewicz (2020)
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arXiv
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| Autores principales: | , , |
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| Formato: | Preprint |
| Publicado: |
2020
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| _version_ | 1866917465129222144 |
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| author | Kovács, Solt Li, Housen Bühlmann, Peter |
| author_facet | Kovács, Solt Li, Housen Bühlmann, Peter |
| contents | In this discussion, we compare the choice of seeded intervals and that of random intervals for change point segmentation from practical, statistical and computational perspectives. Furthermore, we investigate a novel estimator of the noise level, which improves many existing model selection procedures (including the steepest drop to low levels), particularly for challenging frequent change point scenarios with low signal-to-noise ratios. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2006_12806 |
| institution | arXiv |
| publishDate | 2020 |
| record_format | arxiv |
| spellingShingle | Seeded intervals and noise level estimation in change point detection: A discussion of Fryzlewicz (2020) Kovács, Solt Li, Housen Bühlmann, Peter Methodology Computation In this discussion, we compare the choice of seeded intervals and that of random intervals for change point segmentation from practical, statistical and computational perspectives. Furthermore, we investigate a novel estimator of the noise level, which improves many existing model selection procedures (including the steepest drop to low levels), particularly for challenging frequent change point scenarios with low signal-to-noise ratios. |
| title | Seeded intervals and noise level estimation in change point detection: A discussion of Fryzlewicz (2020) |
| topic | Methodology Computation |
| url | https://arxiv.org/abs/2006.12806 |