scientific article; zbMATH DE number 5586090
From MaRDI portal
Publication:5323642
zbMath1166.62012MaRDI QIDQ5323642
Publication date: 23 July 2009
Full work available at URL: http://www3.stat.sinica.edu.tw/statistica/J19N2/j19n222/j19n222.html
Title: zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Asymptotic properties of parametric estimators (62F12) Nonparametric regression and quantile regression (62G08) Linear regression; mixed models (62J05) Monte Carlo methods (65C05) Numerical optimization and variational techniques (65K10)
Related Items
Variable selection in quantile varying coefficient models with longitudinal data, Robust methods for inferring sparse network structures, Interquantile shrinkage and variable selection in quantile regression, Stock return predictability: A factor-augmented predictive regression system with shrinkage method, Penalized and constrained LAD estimation in fixed and high dimension, Variable selection for mode regression, Hierarchically penalized quantile regression with multiple responses, Regularization and model selection for quantile varying coefficient model with categorical effect modifiers, Bayesian regularized regression based on composite quantile method, Distributed optimization and statistical learning for large-scale penalized expectile regression, High-Dimensional Heteroscedastic Regression with an Application to eQTL Data Analysis, Inference for single-index quantile regression models with profile optimization, Simultaneous estimation for non-crossing multiple quantile regression with right censored data, Variable selection in censored quantile regression with high dimensional data, Adaptive group Lasso selection in quantile models, Empirical likelihood test for high-dimensional two-sample model, Expectile regression for analyzing heteroscedasticity in high dimension, Variable selection for additive partial linear quantile regression with missing covariates, Identification of Partially Linear Structure in Additive Models with an Application to Gene Expression Prediction from Sequences, Regularized linear censored quantile regression, CONDITIONAL MARGINAL TEST FOR HIGH DIMENSIONAL QUANTILE REGRESSION, A proximal dual semismooth Newton method for zero-norm penalized quantile regression estimator, Penalized principal logistic regression for sparse sufficient dimension reduction, Binary classification via spherical separator by DC programming and DCA, Robust Bayesian regularized estimation based on \(t\) regression model, Bayesian model selection in ordinal quantile regression, Sampling Lasso quantile regression for large-scale data, Variable selection in expectile regression, Penalized empirical likelihood for quantile regression with missing covariates and auxiliary information, Regularized quantile regression under heterogeneous sparsity with application to quantitative genetic traits, Variable selection and parameter estimation via WLAD-SCAD with a diverging number of parameters, Regularized partially functional quantile regression, Handling multicollinearity in quantile regression through the use of principal component regression, Bayesian adaptive Lasso quantile regression, A penalized approach to covariate selection through quantile regression coefficient models, Robust post-selection inference of high-dimensional mean regression with heavy-tailed asymmetric or heteroskedastic errors, Test by adaptive Lasso quantile method for real-time detection of a change-point, Composite quantile regression for massive datasets, Estimation and variable selection for quantile partially linear single-index models, Focused information criterion and model averaging in censored quantile regression, Pseudo-quantile functional data clustering, Large covariance estimation through elliptical factor models, Penalized expectile regression: an alternative to penalized quantile regression, Globally adaptive quantile regression with ultra-high dimensional data, Sparse wavelet estimation in quantile regression with multiple functional predictors, Variable selection in robust semiparametric modeling for longitudinal data, Robust direction identification and variable selection in high dimensional general single-index models, The quantile process under random censoring, Simultaneous variable selection and estimation in semiparametric modeling of longitudinal/clustered data, Variable selection for multicategory SVM via adaptive sup-norm regularization, Weighted composite quantile estimation and variable selection method for censored regression model, Shrinkage estimation for identification of linear components in additive models, Model selection in high-dimensional quantile regression with seamless \(L_0\) penalty, New efficient estimation and variable selection methods for semiparametric varying-coefficient partially linear models, Simultaneous estimation and factor selection in quantile regression via adaptive sup-norm regularization, Model selection in binary and Tobit quantile regression using the Gibbs sampler, A coordinate descent algorithm for computing penalized smooth quantile regression, Oracle properties of SCAD-penalized support vector machine, Significance testing in quantile regression, A note on the consistency of Schwarz's criterion in linear quantile regression with the SCAD penalty, Quadratic approximation on SCAD penalized estimation, Adaptive robust variable selection, Censored quantile regression processes under dependence and penalization, Bayesian quantile regression with mixed discrete and nonignorable missing covariates, Multiple predictingK-fold cross-validation for model selection, Variable selection in quantile regression when the models have autoregressive errors, Robust low-rank multiple kernel learning with compound regularization, DC programming and DCA: thirty years of developments, Oracle inequalities for sparse additive quantile regression in reproducing kernel Hilbert space, Network tail risk estimation in the European banking system, Adaptive varying-coefficient linear quantile model: a profiled estimating equations approach, Advanced algorithms for penalized quantile and composite quantile regression, Quantile regression in varying-coefficient models: non-crossing quantile curves and heteroscedasticity, Bayesian Lasso binary quantile regression, A generalized Newton algorithm for quantile regression models, Generalized \(\ell_1\)-penalized quantile regression with linear constraints, Quantile regression and variable selection for partially linear model with randomly truncated data, Group identification and variable selection in quantile regression, Screening and selection for quantile regression using an alternative measure of variable importance, Strong oracle optimality of folded concave penalized estimation, Bayesian regularized quantile structural equation models, Simultaneous variable selection and parametric estimation for quantile regression, Quantile regression for functional partially linear model in ultra-high dimensions, Conjugate priors and variable selection for Bayesian quantile regression, Learning sparse conditional distribution: an efficient kernel-based approach, Sentiment analysis with covariate-assisted word embeddings, Shrinkage estimation of varying covariate effects based on quantile regression, Kernel density regression, Penalised quantile periodogram for spectral estimation, Simultaneous estimation of linear conditional quantiles with penalized splines, Adaptive sparse group LASSO in quantile regression, Bayesian semiparametric additive quantile regression, Model averaging marginal regression for high dimensional conditional quantile prediction, Nonnegative estimation and variable selection under minimax concave penalty for sparse high-dimensional linear regression models, Adaptive fused LASSO in grouped quantile regression, Quantile regression feature selection and estimation with grouped variables using Huber approximation, Stable portfolio selection strategy for mean-variance-CVaR model under high-dimensional scenarios, Adaptive elastic-net selection in a quantile model with diverging number of variable groups, Tractable Bayesian Variable Selection: Beyond Normality, Jackknife model averaging for quantile regressions, Bayesian analysis for quantile smoothing spline, Assessing quantile prediction with censored quantile regression models, Variable selection in heteroscedastic single-index quantile regression, M-estimation and model identification based on double SCAD penalization, Bayesian tobit quantile regression with penalty, Bayesian bridge quantile regression, Model-based recursive partitioning algorithm to penalized non-crossing multiple quantile regression for the right-censored data, Jackknife model averaging for high‐dimensional quantile regression, Variable selection via composite quantile regression with dependent errors, SCAD‐penalized quantile regression for high‐dimensional data analysis and variable selection, Automatic selection by penalized asymmetric L q -norm in a high-dimensional model with grouped variables, Predictive quantile regression with mixed roots and increasing dimensions: the ALQR approach, Sequential change point detection for high‐dimensional data using nonconvex penalized quantile regression, Rapid penalized likelihood-based outlier detection via heteroskedasticity test, Regularized boxplot via convex clustering, Sparse quantile regression, Efficient sparse portfolios based on composite quantile regression for high-dimensional index tracking, Variable selection in the single-index quantile regression model with high-dimensional covariates, Robust and smoothing variable selection for quantile regression models with longitudinal data, A Bayesian variable selection approach to longitudinal quantile regression, Quantile regression for compositional covariates, Structure learning via unstructured kernel-based M-estimation, Open issues and recent advances in DC programming and DCA, Quantile regression and variable selection for the single-index model, Sparse group variable selection based on quantile hierarchical Lasso, Model selection in quantile regression models, Unnamed Item, Do maternal health problems influence child's worrying status? Evidence from the British Cohort Study, Bayesian variable selection and estimation in maximum entropy quantile regression, Iteratively Reweighted Group Lasso Based on Log-Composite Regularization, Quasi-likelihood and/or robust estimation in high dimensions, Comments on: ``An updated review of goodness-of-fit tests for regression models, Bayesian Lasso-mixed quantile regression, Simultaneous structure estimation and variable selection in partial linear varying coefficient models for longitudinal data, Hierarchically penalized quantile regression, Unnamed Item, Binary quantile regression and variable selection: A new approach, An elastic-net penalized expectile regression with applications, Outlier detection and robust variable selection via the penalized weighted LAD-LASSO method, Modified check loss for efficient estimation via model selection in quantile regression, Sparse Bayesian linear regression using generalized normal priors
