High-dimensional generalizations of asymmetric least squares regression and their applications
From MaRDI portal
Publication:510692
DOI10.1214/15-AOS1431zbMath1364.62185MaRDI QIDQ510692
Publication date: 13 February 2017
Published in: The Annals of Statistics (Search for Journal in Brave)
regularizationlinear modelheteroscedasticityhigh-dimensional datavariable selectionasymmetric least squares
Related Items (28)
Robust estimation and shrinkage in ultrahigh dimensional expectile regression with heavy tails and variance heterogeneity ⋮ High-dimensional expectile regression incorporating graphical structure among predictors ⋮ Variable selection in high-dimensional linear model with possibly asymmetric errors ⋮ Expectile regression for analyzing heteroscedasticity in high dimension ⋮ A proximal dual semismooth Newton method for zero-norm penalized quantile regression estimator ⋮ Multiple change-points estimation in linear regression models via an adaptive Lasso expectile loss function ⋮ Real-time detection of a change-point in a linear expectile model ⋮ An improved algorithm for high-dimensional continuous threshold expectile model with variance heterogeneity ⋮ Penalized expectile regression: an alternative to penalized quantile regression ⋮ Functional additive expectile regression in the reproducing kernel Hilbert space ⋮ Variable selection and debiased estimation for single‐index expectile model ⋮ The rate of convergence for sparse and low-rank quantile trace regression ⋮ Retire: robust expectile regression in high dimensions ⋮ Cross-Fitted Residual Regression for High-Dimensional Heteroscedasticity Pursuit ⋮ Parametric expectile regression and its application for premium calculation ⋮ Expectile trace regression via low-rank and group sparsity regularization ⋮ Communication‐efficient low‐dimensional parameter estimation and inference for high‐dimensional Lp$$ {L}^p $$‐quantile regression ⋮ Penalized likelihood and multiple testing ⋮ Regression analysis: likelihood, error and entropy ⋮ Efficient estimation in expectile regression using envelope models ⋮ The \(k\)th power expectile regression ⋮ Variable selection for high-dimensional regression models with time series and heteroscedastic errors ⋮ Optimal model averaging estimator for expectile regressions ⋮ Group penalized quantile regression ⋮ An elastic-net penalized expectile regression with applications ⋮ Statistical inference in the partial functional linear expectile regression model ⋮ Local linear estimate of the functional expectile regression ⋮ Nonparametric estimation of expectile regression in functional dependent data
This page was built for publication: High-dimensional generalizations of asymmetric least squares regression and their applications
