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A Brief Survey of Bandwidth Selection for Density Estimation
Abstract
There has been major progress in recent years in data-based bandwidth selection for kernel density estimation. Some “second generation” methods, including plug-in and smoothed bootstrap techniques, have been developed that are far superior to well-known “first generation” methods, such as rules of thumb, least squares cross-validation, and biased cross-validation. We recommend a “solve-the-equation” plug-in bandwidth selector as being most reliable in terms of overall performance. This article is intended to provide easy accessibility to the main ideas for nonexperts.
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Cites
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Botev, Z. I., Grotowski, J. F., & Kroese, D. P. (2010) · The Annals of Statistics · doi:10.1214/10-aos799 · Cited by 1,689
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Effects of Sample Size on Kernel Home Range Estimates
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Metadata
- Authors
- Jones, M. C., Marron, J. S., & Sheather, S. J.
- Venue
- Journal of the American Statistical Association
- Publisher
- Informa UK Limited
- Published
- 1996-03
- Volume
- 91
- Issue
- 433
- Pages
- 401-407
- ISSN
- 0162-1459 (ISSN-L)
- 1537-274X
- OpenAlex
- W2108447811
- Cited by
- 1,280
- References
- 1
- FWCI
- 20.98
- Type
- journal article
- Language
- en
- Open access
- closed
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- Jones, M. C., Marron, J. S., & Sheather, S. J. (1996). A Brief Survey of Bandwidth Selection for Density Estimation. Journal of the American Statistical Association. https://doi.org/10.1080/01621459.1996.10476701
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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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