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SiZer for Exploration of Structures in Curves
Abstract
In the use of smoothing methods in data analysis, an important question is which observed features are “really there,” as opposed to being spurious sampling artifacts. An approach is described based on scale-space ideas originally developed in the computer vision literature. Assessment of Significant ZERo crossings of derivatives results in the SiZer map, a graphical device for display of significance of features with respect to both location and scale. Here “scale” means “level of resolution”; that is, “bandwidth.”
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Cited by
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Metadata
- Authors
- Chaudhuri, P., & Marron, J. S.
- Venue
- Journal of the American Statistical Association
- Publisher
- Informa UK Limited
- Published
- 1999-09
- Volume
- 94
- Issue
- 447
- Pages
- 807-823
- ISSN
- 0162-1459 (ISSN-L)
- 1537-274X
- OpenAlex
- W2099416373
- Cited by
- 591
- References
- 0
- FWCI
- 13.87
- Type
- journal article
- Language
- en
- Open access
- closed
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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