Revisiting the predictive potential of Kernel principal components

Jones, Benjamin ORCID: https://orcid.org/0000-0002-6058-9692 and Artemiou, Andreas ORCID: https://orcid.org/0000-0002-7501-4090 2021. Revisiting the predictive potential of Kernel principal components. Statistics and Probability Letters 171 , 109019. 10.1016/j.spl.2020.109019

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Abstract

In this short note, recent results on the predictive power of kernel principal component in a regression setting are extended in two ways: (1) in the model-free setting, we relax a conditional independence model assumption to obtain a stronger result; and (2) the model-free setting is also extended in the infinite-dimensional setting.

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	Mathematics
Subjects:	Q Science > QA Mathematics
Additional Information:	This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/)
Publisher:	Elsevier
ISSN:	0167-7152
Funders:	EPSRC
Date of First Compliant Deposit:	7 December 2020
Date of Acceptance:	5 December 2020
Last Modified:	21 May 2023 14:37
URI:	https://orca.cardiff.ac.uk/id/eprint/136829

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