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On cross-validation in kernel and partitioning regression estimation

✍ Scribed by Harro Walk

Publisher: Elsevier Science
Year: 2002
Tongue: English
Weight: 134 KB
Volume: 59
Category: Article
ISSN: 0167-7152
DOI: 10.1016/s0167-7152(02)00103-7

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✦ Synopsis

The paper deals with the approximation of the best deterministic choice (minimizing mean integrated squared error) of the parameter in naive kernel and cubic partitioning regression estimation by cross-validation. The result is essentially distribution-free.

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