Robust estimation and shrinkage in ultrahigh dimensional expectile regression with heavy tails and variance heterogeneity

DOI10.1007/s00362-021-01227-2OpenAlexW3136562446MaRDI QIDQ2122800

Yi Zhang, Guan'ao Yan, Jun Zhao

Publication date: 7 April 2022

Published in: Statistical Papers (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1909.09302

zbMATH Keywords

heterogeneityheavy-tailed distributionhigh dimensionexpectile regressionrobust regularization

Mathematics Subject Classification ID

Statistics (62-XX)

Related Items (4)

Point forecasting and forecast evaluation with generalized Huber loss ⋮ An improved algorithm for high-dimensional continuous threshold expectile model with variance heterogeneity ⋮ Data-driven and distribution-free estimation of tailed-related risks for GARCH models using composite asymmetric least squares regression ⋮ Expectile trace regression via low-rank and group sparsity regularization

Uses Software

• GLIM
• CVX
• robustbase
• CVXR
• RobStatTM

Cites Work

• Unnamed Item
• Unnamed Item
• Nearly unbiased variable selection under minimax concave penalty
• Asymmetric Least Squares Estimation and Testing
• Geoadditive expectile regression
• High-dimensional generalizations of asymmetric least squares regression and their applications
• Fast global convergence of gradient methods for high-dimensional statistical recovery
• Concentration inequalities and model selection. Ecole d'Eté de Probabilités de Saint-Flour XXXIII -- 2003.
• One-step sparse estimates in nonconcave penalized likelihood models
• Robust regression based on infinitesimal neighbourhoods
• Expectile regression for analyzing heteroscedasticity in high dimension
• Robust and sparse estimators for linear regression models
• Nonlinear expectile regression with application to value-at-risk and expected shortfall estimation
• Robust variable selection in high-dimensional varying coefficient models based on weighted composite quantile regression
• Strong oracle optimality of folded concave penalized estimation
• Quantiles, expectiles and splines
• COHERENCE AND ELICITABILITY
• Graph Implementations for Nonsmooth Convex Programs
• Minimax Aspects of Bounded-Influence Regression
• On the Estimation of Production Frontiers: Maximum Likelihood Estimation of the Parameters of a Discontinuous Density Function
• Asymmetric least squares regression estimation: A nonparametric approach^∗
• Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties
• Robust Statistics
• Quantile Regression for Analyzing Heterogeneity in Ultra-High Dimension
• Expectile and quantile regression—David and Goliath?
• A New Principle for Tuning-Free Huber Regression
• Estimation of High Dimensional Mean Regression in the Absence of Symmetry and Light Tail Assumptions
• Regularized M-estimators with nonconvexity: Statistical and algorithmic theory for local optima
• Robust Estimation of a Location Parameter

This page was built for publication: Robust estimation and shrinkage in ultrahigh dimensional expectile regression with heavy tails and variance heterogeneity