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Revisiting the predictive potential of Kernel principal components

Jones, Benjamin and Artemiou, Andreas 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: 18 Mar 2021 10:38
URI: http://orca.cf.ac.uk/id/eprint/136829

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