Explicit solutions for the asymptotically optimal bandwidth in cross-validation

Abstract We show that least-squares cross-validation methods share a common structure that has an explicit asymptotic solution, when the chosen kernel is asymptotically separable in bandwidth and data. For density estimation with a multivariate Student-t(ν) kernel, the cross-validation criterion bec...

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Bibliographic Details

Published in:	Biometrika Vol. 111; no. 3; pp. 809 - 823
Main Authors:	Abadir, Karim M, Lubrano, Michel
Format:	Journal Article
Language:	English
Published:	Oxford Oxford University Press 01-09-2024 Oxford Publishing Limited (England) Oxford University Press (OUP)
Subjects:	Asymptotic methods Bivariate analysis Colleges & universities Density Economics and Finance Humanities and Social Sciences Multivariate analysis Polynomials Academic wage distribution Nonparametric density estimation Bandwidth choice Explicit analytical solution Cross-validation
Online Access:	Get full text
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