Variable selection in functional additive regression models
From MaRDI portal
Publication:2418050
DOI10.1007/s00180-018-0844-5zbMath1417.62077arXiv1801.00736OpenAlexW2609111671WikidataQ129161194 ScholiaQ129161194MaRDI QIDQ2418050
Manuel Febrero-Bande, Wenceslao González Manteiga, Manuel Oviedo de la Fuente
Publication date: 3 June 2019
Published in: Computational Statistics (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1801.00736
Computational methods for problems pertaining to statistics (62-08) Nonparametric regression and quantile regression (62G08) Asymptotic properties of nonparametric inference (62G20)
Related Items (6)
Editorial on the special issue on functional data analysis and related topics ⋮ Sharp lower bound for regression with measurement errors and its implication for ill-posedness of functional regression ⋮ A Critical Review of LASSO and Its Derivatives for Variable Selection Under Dependence Among Covariates ⋮ On optimal regression trees to detect critical intervals for multivariate functional data ⋮ Optimum Scale Selection for 3D Point Cloud Classification through Distance Correlation ⋮ Variable selection in functional regression models: a review
Uses Software
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Partial distance correlation with methods for dissimilarities
- Measuring and testing dependence by correlation of distances
- The Adaptive Lasso and Its Oracle Properties
- Distance covariance in metric spaces
- The distance correlation \(t\)-test of independence in high dimension
- Semiparametric regression models with additive nonparametric components and high dimensional parametric components
- Improved variable selection with forward-lasso adaptive shrinkage
- Estimation and variable selection for generalized additive partial linear models
- Component selection and smoothing in multivariate nonparametric regression
- Additive prediction and boosting for functional data
- Estimating the dimension of a model
- Least angle regression. (With discussion)
- Generalized additive models for functional data
- Generalized Additive Models: Some Applications
- Maximum likelihood identification of Gaussian autoregressive moving average models
- Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties
- Boosting With theL2Loss
- Variable selection in regression using maximal correlation and distance correlation
- Functional Additive Models
- Some Comments on C P
- Stable and Efficient Multiple Smoothing Parameter Estimation for Generalized Additive Models
- Estimation and variable selection for semiparametric additive partial linear models
This page was built for publication: Variable selection in functional additive regression models