Bandwidth Selection in Nonparametric Regression with Large Sample Size

Bandwidth Selection in Nonparametric Regression with Large Sample Size

In the context of nonparametric regression estimation, the behaviour of kernel methods such as the Nadaraya-Watson or local linear estimators is heavily influenced by the value of the bandwidth parameter, which determines the trade-off between bias and variance. This clearly implies that the selecti...

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Bibliographic Details
Main Authors: Daniel Barreiro-Ures, Ricardo Cao, Mario Francisco-Fernández
Format: Article
Language:English
Published: MDPI AG 2018-09-01
Series:Proceedings
Subjects:
nonparametric
regression
bandwidth
Big Data
cross-validation
subsampling
Online Access:http://www.mdpi.com/2504-3900/2/18/1166

Internet

http://www.mdpi.com/2504-3900/2/18/1166

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