Adaptive functional linear regression via functional principal component analysis and block thresholding

DOI10.5705/ss.202017.0099zbMath1406.62062OpenAlexW2758232140MaRDI QIDQ4558594

Harrison H. Zhou, T. Tony Cai, Linjun Zhang

Publication date: 22 November 2018

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

Full work available at URL: https://semanticscholar.org/paper/2c0403e8e9dbf4f7b3d357bbb845e6e85c8b8634

zbMATH Keywords

rate of convergencesmoothingeigenvaluespectral decompositioneigenfunctionadaptive estimationlinear regressionminimax estimationfunctional data analysisfunctional principal component analysisblock thresholdingslope function

Mathematics Subject Classification ID

Factor analysis and principal components; correspondence analysis (62H25) Linear regression; mixed models (62J05) Inference from stochastic processes and spectral analysis (62M15)

Related Items (3)

Nonparametric estimation of a quantile density function under L_p risk via block thresholding method ⋮ Estimation and inference in partially functional linear regression with multiple functional covariates ⋮ Framelet block thresholding estimator for sparse functional data

This page was built for publication: Adaptive functional linear regression via functional principal component analysis and block thresholding