A short note on optimal bandwidth selection for kernel estimators
For kernel estimators of an unknown density it has been proposed to use a data-based bandwidth which is as close to the (nonrandom, unknown) minimiser of the Mean Integrated Squared Error as possible. In this note it will be shown that this strategy of bandwidth selection is not optimal.
Gespeichert in:
| 1. Verfasser: | |
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| Dokumenttyp: | Article (Journal) |
| Sprache: | Englisch |
| Veröffentlicht: |
1990
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| In: |
Statistics & probability letters
Year: 1990, Jahrgang: 9, Heft: 1, Pages: 23-25 |
| ISSN: | 1879-2103 |
| DOI: | 10.1016/0167-7152(90)90090-T |
| Online-Zugang: | Verlag, Volltext: http://dx.doi.org/10.1016/0167-7152(90)90090-T Verlag, Volltext: http://www.sciencedirect.com/science/article/pii/016771529090090T |
| Verfasserangaben: | Enno Mammen |
MARC
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| 520 | |a For kernel estimators of an unknown density it has been proposed to use a data-based bandwidth which is as close to the (nonrandom, unknown) minimiser of the Mean Integrated Squared Error as possible. In this note it will be shown that this strategy of bandwidth selection is not optimal. | ||
| 650 | 4 | |a kernel estimator | |
| 650 | 4 | |a bandwidth selection | |
| 650 | 4 | |a Nonparametric density estimation | |
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