Variable selection in functional regression models: a review
type: Item
instance of: scholarly article
title: Variable selection in functional regression models: a review
zbMATH Open document ID: 1493.62293
author: Silvia Novo
author: Philippe Vieu
author: Germán Aneiros
published in: Journal of Multivariate Analysis
publication date: 2022-01-03T00:00:00Z
Mathematics Subject Classification ID: 62H12
Mathematics Subject Classification ID: 62R10
zbMATH DE Number: 7451368
zbMATH Keywords: functional data analysis
zbMATH Keywords: regression
zbMATH Keywords: variable selection
describes a project that uses: fda (R)
describes a project that uses: alr3
MaRDI profile type: Publication
full work available at URL: j.jmva.2021.104871
OpenAlex ID: W3208141052
cites work: Big and complex data analysis. Methodologies and applications
cites work: Cross-validated estimations in the single-functional index model
cites work: Nonlinear regression modeling via regularized radial basis function networks
cites work: Recent advances in functional data analysis and high-dimensional statistics
cites work: Editorial for the special issue on functional data analysis and related topics
cites work: Variable selection in partial linear regression with functional covariate
cites work: Variable selection in infinite-dimensional problems
cites work: Partial linear modelling with multi-functional covariates
cites work: Comments on: ``Probability enhanced effective dimension reduction for classifying sparse functional data''
cites work: An RKHS model for variable selection in functional linear regression
cites work: Heuristics of instability and stabilization in model selection
cites work: The Dantzig selector: statistical estimation when \(p\) is much larger than \(n\). (With discussions and rejoinder).
cites work: Consistent variable selection for functional regression models
cites work: A partial overview of the theory of statistics with functional data
cites work: A practical guide to splines.
cites work: Least angle regression. (With discussion)
cites work: Q3262547
cites work: Q3125064
cites work: Functional additive regression
cites work: Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties
cites work: Sure Independence Screening for Ultrahigh Dimensional Feature Space
cites work: A Selective Overview of Variable Selection in High Dimensional Feature Space (Invited Review Article)
cites work: Nonconcave penalized likelihood with a diverging number of parameters.
cites work: Variable selection in functional additive regression models
cites work: Most-predictive design points for functional data predictors
cites work: Nonparametric functional data analysis. Theory and practice.
cites work: A Statistical View of Some Chemometrics Regression Tools
cites work: Regressions by Leaps and Bounds
cites work: Q4344410
cites work: An introduction to recent advances in high/infinite dimensional statistics
cites work: Properties of principal component methods for functional and longitudinal data analysis
cites work: Inference of Genetic Networks from Time Course Expression Data Using Functional Regression with Lasso Penalty
cites work: Asymptotic properties of bridge estimators in sparse high-dimensional regression models
cites work: Variable selection in nonparametric additive models
cites work: Robust shrinkage estimation and selection for functional multiple linear model through LAD loss
cites work: Covariate assisted screening and estimation
cites work: Functional linear regression with points of impact
cites work: Factor models and variable selection in high-dimensional regression analysis
cites work: Partially functional linear regression in high dimensions
cites work: Q3431917
cites work: Feature Screening via Distance Correlation Learning
cites work: Shrinkage estimation and selection for multiple functional regression
cites work: Quantile regression for functional partially linear model in ultra-high dimensions
cites work: Variable and boundary selection for functional data via multiclass logistic regression modeling
cites work: Sparse group lasso for multiclass functional logistic regression models
cites work: Variable selection for functional regression models via the \(L_1\) regularization
cites work: Fractals with point impact in functional linear regression
cites work: High-dimensional additive modeling
cites work: High-dimensional graphs and variable selection with the Lasso
cites work: Using random subspace method for prediction and variable importance assessment in linear regression
cites work: Peter Hall, functional data analysis and random objects
cites work: Sparse semiparametric regression when predictors are mixture of functional and high-dimensional variables
cites work: Fast and efficient algorithms for sparse semiparametric bifunctional regression
cites work: A review of Bayesian variable selection methods: what, how and which
cites work: Functional data analysis.
cites work: The role of statistics in the era of big data
cites work: A note on variable selection in functional regression via random subspace method
cites work: Measuring and testing dependence by correlation of distances
cites work: Q4864293
cites work: On dimension reduction models for functional data

Variable selection in functional regression models: a review (cites work)
cites work: Q3311506

Variable selection in functional regression models: a review (cites work)
cites work: Model Selection and Estimation in Regression with Grouped Variables

Variable selection in functional regression models: a review (cites work)
cites work: The composite absolute penalties family for grouped and hierarchical variable selection

Variable selection in functional regression models: a review (cites work)
cites work: A functional generalized linear model with curve selection in cervical pre-cancer diagnosis using fluorescence spectroscopy

Variable selection in functional regression models: a review (cites work)
cites work: A Bayesian Hierarchical Model for Classification with Selection of Functional Predictors

Variable selection in functional regression models: a review (cites work)
cites work: The Adaptive Lasso and Its Oracle Properties

Variable selection in functional regression models: a review (cites work)
cites work: Regularization and Variable Selection Via the Elastic Net

Variable selection in functional regression models: a review (DOI)
DOI: 10.1016/J.JMVA.2021.104871