Estimation of Sparse Functional Additive Models with Adaptive Group LASSO
DOI10.5705/ss.202017.0491zbMath1456.62150OpenAlexW2954280123MaRDI QIDQ5134473
Peijun Sang, Jiguo Cao, Liang-Liang Wang
Publication date: 16 November 2020
Published in: Statistica Sinica (Search for Journal in Brave)
Full work available at URL: https://semanticscholar.org/paper/a99941eeb860665500483cd6cd77850ac808ceac
smoothing splinefunctional data analysisgroup Lassofunctional principal component analysisfunctional linear model
Factor analysis and principal components; correspondence analysis (62H25) Ridge regression; shrinkage estimators (Lasso) (62J07) Functional data analysis (62R10) Linear regression; mixed models (62J05)
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Cites Work
- The Adaptive Lasso and Its Oracle Properties
- Inference for functional data with applications
- Single and multiple index functional regression models with nonparametric link
- Component selection and smoothing in multivariate nonparametric regression
- Variable selection in nonparametric additive models
- The dimensionality reduction principle for generalized additive models
- Additive regression and other nonparametric models
- Generalized additive models
- Flexible smoothing with \(B\)-splines and penalties. With comments and a rejoinder by the authors
- Estimator selection and combination in scalar-on-function regression
- Estimating functional linear mixed-effects regression models
- Sparse estimation for functional semiparametric additive models
- Functional data analysis in ecosystem research: the decline of Oweekeno Lake sockeye salmon and wannock river flow
- Generalized functional linear models
- Functional data analysis.
- Sparse Additive Ordinary Differential Equations for Dynamic Gene Regulatory Network Modeling
- Partially Linear Functional Additive Models for Multivariate Functional Data
- Functional quadratic regression
- Continuously additive models for nonlinear functional regression
- Functional Additive Models
- Model Selection and Estimation in Regression with Grouped Variables
- Structured Functional Additive Regression in Reproducing Kernel Hilbert Spaces
- The elements of statistical learning. Data mining, inference, and prediction
- A practical guide to splines.
- Methods for Scalar‐on‐Function Regression
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