Functional Sliced Inverse Regression in a Reproducing Kernel Hilbert Space: a Theoretical Connection to Functional Linear Regression

DOI10.5705/SS.202017.0277zbMath1444.62169OpenAlexW2811484825WikidataQ130173477 ScholiaQ130173477MaRDI QIDQ5220356

Guochang Wang, Heng Lian

Publication date: 16 March 2020

Published in: Statistica Sinica (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.5705/ss.202017.0277

zbMATH Keywords

convergence ratefunctional datasliced inverse regression

Mathematics Subject Classification ID

Factor analysis and principal components; correspondence analysis (62H25) Functional data analysis (62R10) Linear regression; mixed models (62J05) Hilbert spaces with reproducing kernels (= (proper) functional Hilbert spaces, including de Branges-Rovnyak and other structured spaces) (46E22)

Related Items (4)

Functional sufficient dimension reduction based on weighted method ⋮ Covariance estimation error of incomplete functional data under RKHS framework ⋮ A new RKHS-based global testing for functional linear model ⋮ New estimation for heteroscedastic single-index measurement error models

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