Sparse estimation in functional linear regression

DOI10.1016/j.jmva.2011.08.005zbMath1236.62032OpenAlexW2135525924MaRDI QIDQ764470

Eun Ryung Lee, Byeong U. Park

Publication date: 13 March 2012

Published in: Journal of Multivariate Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jmva.2011.08.005

zbMATH Keywords

sparsityfunctional data analysisMCPSCADadaptive LASSOoracle propertiesKarhunenfunctional principal components analysisLoève expansionpenalized least squares regression

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Factor analysis and principal components; correspondence analysis (62H25) Ridge regression; shrinkage estimators (Lasso) (62J07) Linear regression; mixed models (62J05) Applications of statistics to environmental and related topics (62P12)

Related Items

An introduction to recent advances in high/infinite dimensional statistics ⋮ Feature selection for functional data ⋮ Statistical inference in sparse high-dimensional additive models ⋮ Estimator selection and combination in scalar-on-function regression ⋮ An adaptive group Lasso approach for domain selection in functional generalized linear models ⋮ Robust estimation for partial functional linear regression models based on FPCA and weighted composite quantile regression ⋮ Methods for Scalar‐on‐Function Regression ⋮ Non-asymptotic adaptive prediction in functional linear models ⋮ Fréchet distance-based cluster analysis for multi-dimensional functional data ⋮ Locally Sparse Function-on-Function Regression ⋮ Unnamed Item ⋮ Sparse clustering of functional data ⋮ Functional linear regression for functional response via sparse basis selection ⋮ Smoothly adaptively centered ridge estimator

Uses Software

• fda (R)

Cites Work

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