期刊
INTERNATIONAL STATISTICAL REVIEW
卷 82, 期 2, 页码 243-274出版社
WILEY
DOI: 10.1111/insr.12039
关键词
Kernel regression; bandwidth selection; plug-in; cross-validation
资金
- Spanish 'Ministerio de Ciencia e Innovacion' [MTM2008-03010]
- Swiss Science Foundation [100018-140295]
- Swiss National Science Foundation (SNF) [100018_140295] Funding Source: Swiss National Science Foundation (SNF)
Over the last decades, several methods for selecting the bandwidth have been introduced in kernel regression. They differ quite a bit, and although there already exist more selection methods than for any other regression smoother, one can still observe coming up new ones. Given the need of automatic data-driven bandwidth selectors for applied statistics, this review is intended to explain and, above all, compare these methods. About 20 different selection methods have been revised, implemented and compared in an extensive simulation study.
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