Weighted least squares methods for prediction in the functional data linear model

DOI10.1214/09-EJS379zbMath1326.62151arXiv0902.3319MaRDI QIDQ1952006

Aurore Delaigle, Tatiyana V. Apanasovich, Hall, Peter

Publication date: 27 May 2013

Published in: Electronic Journal of Statistics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/0902.3319

zbMATH Keywords

rate of convergencemean squared erroreigenvectorprincipal component analysiscross-validationeigenfunctionorthogonal seriesfunctional data analysisfunctional linear regressionweighted linear regression

Mathematics Subject Classification ID

Linear regression; mixed models (62J05) Nonparametric estimation (62G05)

Related Items

Methods for Scalar‐on‐Function Regression, Wavelet-based LASSO in functional linear quantile regression, Functional linear regression after spline transformation, Asymptotic equivalence of functional linear regression and a white noise inverse problem, Improving prediction performance of stellar parameters using functional models, Nonparametric time series forecasting with dynamic updating, Forecasting functional time series, Robust functional linear regression based on splines, Robust estimation for a general functional single index model via quantile regression

Uses Software

• fda (R)

Cites Work

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