A Review and Comparison of Bandwidth Selection Methods for Kernel Regression

Max Köhler, Anja Schindler and Stefan Sperlich
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Max Köhler: Georg-August-University Göttingen
Anja Schindler: Georg-August-University Göttingen
Stefan Sperlich: Université de Genéve

No 95, Courant Research Centre: Poverty, Equity and Growth - Discussion Papers from Courant Research Centre PEG

Abstract: Over the last four decades, several methods for selecting the smoothing parameter, generally called 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 we can still see coming up new ones. Given the need of automatic data-driven bandwidth selectors for applied statistics, this review is intended to explain and compare these methods.

Keywords: Kernel regression estimation; Bandwidth Selection; Plug-in; Cross Validation (search for similar items in EconPapers)
Date: 2011-09-13
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Related works:
Journal Article: A Review and Comparison of Bandwidth Selection Methods for Kernel Regression (2014)
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