Wavelet-based LASSO in functional linear quantile regression

DOI10.1080/00949655.2019.1583228OpenAlexW2919563576MaRDI QIDQ5107381

Bei Jiang, Xing-Cai Zhou, Giseon Heo, Li Zhang, Shimei Yu, Yafei Wang, Linglong Kong

Publication date: 27 April 2020

Published in: Journal of Statistical Computation and Simulation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/00949655.2019.1583228

zbMATH Keywords

waveletsADMMquantile regressionfunctional data analysisLASSOADHD

Mathematics Subject Classification ID

Statistics (62-XX)

Related Items

Function-on-function partial quantile regression ⋮ Composite quantile estimation in partial functional linear regression model based on polynomial spline

Uses Software

• quantreg
• wavethresh
• flare
• rwt
• RWT

Cites Work

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• Distributed Optimization and Statistical Learning via the Alternating Direction Method of Multipliers
• Nearly unbiased variable selection under minimax concave penalty
• The Adaptive Lasso and Its Oracle Properties
• Regularized 3D functional regression for brain image data via Haar wavelets
• Methodology and theory for partial least squares applied to functional data
• Composite quantile regression and the oracle model selection theory
• A dual algorithm for the solution of nonlinear variational problems via finite element approximation
• Wavelets, approximation, and statistical applications
• Functional linear model
• An interior point algorithm for nonlinear quantile regression
• Weighted least squares methods for prediction in the functional data linear model
• Generalized functional linear models
• Multiplier and gradient methods
• A Selective Overview of Variable Selection in High Dimensional Feature Space (Invited Review Article)
• Functional Principal Component Regression and Functional Partial Least Squares
• Regression Quantiles
• Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties
• Quantile regression in functional linear semiparametric model
• Local Composite Quantile Regression Smoothing: An Efficient and Safe Alternative to Local Polynomial Regression
• Penalized Composite Quasi-Likelihood for Ultrahigh Dimensional Variable Selection
• Sparse group variable selection based on quantile hierarchical Lasso
• Functional Additive Models
• Model Selection and Estimation in Regression with Grouped Variables