Variable selection in infinite-dimensional problems

DOI10.1016/j.spl.2014.06.025zbMath1320.62163OpenAlexW2076258896MaRDI QIDQ466987

Philippe Vieu, Germán Aneiros-Pérez

Publication date: 3 November 2014

Published in: Statistics \& Probability Letters (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.spl.2014.06.025

zbMATH Keywords

variable selectionfunctional data analysishigh-dimensional problempartitioning variable selection procedure

Mathematics Subject Classification ID

Asymptotic properties of parametric estimators (62F12) Linear regression; mixed models (62J05)

Related Items (44)

An introduction to recent advances in high/infinite dimensional statistics ⋮ Supervised singular value decomposition and its asymptotic properties ⋮ COBRA: a combined regression strategy ⋮ Weak convergence of discretely observed functional data with applications ⋮ Consistent variable selection for functional regression models ⋮ Kriging for Hilbert-space valued random fields: the operatorial point of view ⋮ Sharp minimax tests for large Toeplitz covariance matrices with repeated observations ⋮ Combining a relaxed EM algorithm with Occam's razor for Bayesian variable selection in high-dimensional regression ⋮ Feature selection for functional data ⋮ Direct shrinkage estimation of large dimensional precision matrix ⋮ Worst possible sub-directions in high-dimensional models ⋮ Multivariate functional linear regression and prediction ⋮ An adaptive group Lasso approach for domain selection in functional generalized linear models ⋮ High dimensional discrimination analysis via a semiparametric model ⋮ Penalized spline estimation in the partially linear model ⋮ Robust estimation for varying index coefficient models ⋮ On dimension reduction models for functional data ⋮ Selective inference after likelihood- or test-based model selection in linear models ⋮ On the Use of Reproducing Kernel Hilbert Spaces in Functional Classification ⋮ Variable selection and parameter estimation with the Atan regularization method ⋮ Selection of time instants and intervals with support vector regression for multivariate functional data ⋮ Fast and efficient algorithms for sparse semiparametric bifunctional regression ⋮ Lasso in Infinite dimension: application to variable selection in functional multivariate linear regression ⋮ Sparse nonparametric model for the detection of impact points of a functional variable ⋮ On optimal regression trees to detect critical intervals for multivariate functional data ⋮ Fréchet distance-based cluster analysis for multi-dimensional functional data ⋮ Selected statistical methods of data analysis for multivariate functional data ⋮ Recent advances in functional data analysis and high-dimensional statistics ⋮ An RKHS model for variable selection in functional linear regression ⋮ Optimal shrinkage estimator for high-dimensional mean vector ⋮ Variable Selection in Semiparametric Bi-functional Models ⋮ Robust functional sliced inverse regression ⋮ A novel framework for joint sparse clustering and alignment of functional data ⋮ Sparse clustering of functional data ⋮ Interpretable sparse SIR for functional data ⋮ Asymptotic properties of concave \(L_1\)-norm group penalties ⋮ Comments on: ``Probability enhanced effective dimension reduction for classifying sparse functional data ⋮ Partial linear modelling with multi-functional covariates ⋮ Variable selection in functional regression models: a review ⋮ Sparse nonparametric model for regression with functional covariate ⋮ A note on variable selection in functional regression via random subspace method ⋮ Feature extraction for functional time series: theory and application to NIR spectroscopy data ⋮ Uniform in bandwidth consistency for various kernel estimators involving functional data ⋮ Interval-wise testing for functional data

Uses Software

• fda (R)

Cites Work

• Unnamed Item
• Unnamed Item
• Inference for functional data with applications
• High-dimensional additive modeling
• Applied functional data analysis. Methods and case studies
• Nonconcave penalized likelihood with a diverging number of parameters.
• Least angle regression. (With discussion)
• Simultaneous analysis of Lasso and Dantzig selector
• Asymptotic properties of bridge estimators in sparse high-dimensional regression models
• The Dantzig selector: statistical estimation when \(p\) is much larger than \(n\). (With discussions and rejoinder).
• Functional data analysis.
• Nonparametric functional data analysis. Theory and practice.
• Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties
• Asymptotic oracle properties of SCAD-penalized least squares estimators
• Model Selection and Estimation in Regression with Grouped Variables

This page was built for publication: Variable selection in infinite-dimensional problems