Optimal prediction of quantile functional linear regression in reproducing kernel Hilbert spaces

DOI10.1016/J.JSPI.2020.06.010zbMath1455.62232OpenAlexW3082639578MaRDI QIDQ826973

Heng Lian, Wenqi Lu, Rui Li, Zhong-yi Zhu

Publication date: 6 January 2021

Published in: Journal of Statistical Planning and Inference (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jspi.2020.06.010

zbMATH Keywords

quantile regressionconvergence rateRademacher complexityprediction risk

Mathematics Subject Classification ID

Inference from stochastic processes and prediction (62M20) Nonparametric regression and quantile regression (62G08) Factor analysis and principal components; correspondence analysis (62H25) Functional data analysis (62R10) Linear regression; mixed models (62J05) Monte Carlo methods (65C05)

Related Items (2)

Partially linear functional quantile regression in a reproducing kernel Hilbert space ⋮ Quantile trace regression via nuclear norm regularization

Uses Software

• fda (R)

Cites Work

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