Optimal prediction for high-dimensional functional quantile regression in reproducing kernel Hilbert spaces
type: Item
instance of: scholarly article
title: Optimal prediction for high-dimensional functional quantile regression in reproducing kernel Hilbert spaces
zbMATH Open document ID: 1472.62177
author: Guangren Yang
author: Xiao Hui Liu
author: Heng Lian
published in: Journal of Complexity
publication date: 2021-09-02T00:00:00Z
Mathematics Subject Classification ID: 62R10
Mathematics Subject Classification ID: 62M20
Mathematics Subject Classification ID: 62G08
Mathematics Subject Classification ID: 62C20
Mathematics Subject Classification ID: 46E22
zbMATH DE Number: 7390178
zbMATH Keywords: functional data
zbMATH Keywords: minimax rate
zbMATH Keywords: quantile regression
zbMATH Keywords: reproducing kernel Hilbert space
MaRDI profile type: Publication
full work available at URL: j.jco.2021.101568
OpenAlex ID: W3152192878
cites work: Cross-validated estimations in the single-functional index model
cites work: Local Rademacher complexities
cites work: \(\ell_1\)-penalized quantile regression in high-dimensional sparse models
cites work: Prediction in functional linear regression
cites work: Minimax and Adaptive Prediction for Functional Linear Regression
cites work: Optimal rates for the regularized least-squares algorithm
cites work: Q4438050
cites work: Single and multiple index functional regression models with nonparametric link
cites work: Smoothing splines estimators for functional linear regression
cites work: Presmoothing in functional linear regression
cites work: The functional nonparametric model and applications to spectrometric data
cites work: Methodology and convergence rates for functional linear regression
cites work: Theoretical Foundations of Functional Data Analysis, with an Introduction to Linear Operators
cites work: Estimation in functional linear quantile regression
cites work: Q3413299
cites work: Oracle inequalities in empirical risk minimization and sparse recovery problems. École d'Été de Probabilités de Saint-Flour XXXVIII-2008.
cites work: Sparsity in multiple kernel learning
cites work: Partially functional linear regression in high dimensions
cites work: Nonlinear functional models for functional responses in reproducing kernel hilbert spaces
cites work: Convergence of functional \(k\)-nearest neighbor regression estimate with functional responses
cites work: Optimal Rates for Multi-pass Stochastic Gradient Methods
cites work: Q4637006
cites work: Quantile regression for functional partially linear model in ultra-high dimensions
cites work: Convergence of stochastic processes
cites work: Regression models for functional data by reproducing kernel Hilbert spaces methods
cites work: Minimax-optimal rates for sparse additive models over kernel classes via convex programming
cites work: Fast learning rate of multiple kernel learning: trade-off between sparsity and smoothness
cites work: Q3093390
cites work: Analysis of regularized least squares for functional linear regression model
cites work: Introduction to nonparametric estimation
cites work: Weak convergence and empirical processes. With applications to statistics
cites work: Functional linear regression analysis for longitudinal data
cites work: Regularized partially functional quantile regression
cites work: Structured Functional Additive Regression in Reproducing Kernel Hilbert Spaces
DOI: 10.1016/J.JCO.2021.101568
description: scientific article; zbMATH DE number 7390178