Pages that link to "Item:Q939654"

The following pages link to The sparsity and bias of the LASSO selection in high-dimensional linear regression (Q939654):

Displaying 50 items.

• Minimax-optimal nonparametric regression in high dimensions (Q2343958) (← links)
• A new test for part of high dimensional regression coefficients (Q2348453) (← links)
• An adaptive accelerated proximal gradient method and its homotopy continuation for sparse optimization (Q2352420) (← links)
• Goodness-of-fit tests for high-dimensional Gaussian linear models (Q2380086) (← links)
• Simultaneous analysis of Lasso and Dantzig selector (Q2388978) (← links)
• Lasso for sparse linear regression with exponentially \(\beta\)-mixing errors (Q2407765) (← links)
• D-trace estimation of a precision matrix using adaptive lasso penalties (Q2418368) (← links)
• A nonconvex model with minimax concave penalty for image restoration (Q2420696) (← links)
• Some improved estimation strategies in high-dimensional semiparametric regression models with application to riboflavin production data (Q2423185) (← links)
• A simple homotopy proximal mapping algorithm for compressive sensing (Q2425244) (← links)
• Sup-norm convergence rate and sign concentration property of Lasso and Dantzig estimators (Q2426826) (← links)
• \(\ell_1\)-penalized quantile regression in high-dimensional sparse models (Q2429925) (← links)
• Multi-stage convex relaxation for feature selection (Q2435243) (← links)
• Calibrating nonconvex penalized regression in ultra-high dimension (Q2438760) (← links)
• Estimation in the presence of many nuisance parameters: composite likelihood and plug-in likelihood (Q2447659) (← links)
• Adaptive Lasso estimators for ultrahigh dimensional generalized linear models (Q2453901) (← links)
• High-dimensional graphs and variable selection with the Lasso (Q2500458) (← links)
• Endogeneity in high dimensions (Q2510821) (← links)
• Convergence and sparsity of Lasso and group Lasso in high-dimensional generalized linear models (Q2516626) (← links)
• Nearly optimal Bayesian shrinkage for high-dimensional regression (Q2683046) (← links)
• Sparse estimation via lower-order penalty optimization methods in high-dimensional linear regression (Q2687439) (← links)
• High-dimensional sparse portfolio selection with nonnegative constraint (Q2700403) (← links)
• Multiple structural breaks in cointegrating regressions: a model selection approach (Q2700541) (← links)
• Robust group non-convex estimations for high-dimensional partially linear models (Q2811266) (← links)
• Asymptotic Equivalence of Regularization Methods in Thresholded Parameter Space (Q2861817) (← links)
• On the consistency of feature selection using greedy least squares regression (Q2880890) (← links)
• Variable selection for semiparametric regression models with iterated penalisation (Q2892927) (← links)
• Restricted eigenvalue properties for correlated Gaussian designs (Q2896143) (← links)
• Rate minimaxity of the Lasso and Dantzig selector for the \(l_{q}\) loss in \(l_{r}\) balls (Q2896196) (← links)
• Estimation for high-dimensional linear mixed-effects models using \(\ell_1\)-penalization (Q2911662) (← links)
• Identification of partially linear structure in additive models with an application to gene expression prediction from sequences (Q2912335) (← links)
• Non-asymptotic oracle inequalities for the Lasso and Group Lasso in high dimensional logistic model (Q2954238) (← links)
• On Cross-Validation for Sparse Reduced Rank Regression (Q3120104) (← links)
• A NEW APPROACH TO SELECT THE BEST SUBSET OF PREDICTORS IN LINEAR REGRESSION MODELLING: BI-OBJECTIVE MIXED INTEGER LINEAR PROGRAMMING (Q3122035) (← links)
• Variable selection in high-dimensional partly linear additive models (Q3145401) (← links)
• SCAD-Penalized Least Absolute Deviation Regression in High-Dimensional Models (Q3462376) (← links)
• (Q4558147) (← links)
• Adaptive Lasso for generalized linear models with a diverging number of parameters (Q4605261) (← links)
• (Q4614089) (← links)
• Sure Independence Screening for Ultrahigh Dimensional Feature Space (Q4632602) (← links)
• Stability Selection (Q4632639) (← links)
• Multiple predicting<i>K</i>-fold cross-validation for model selection (Q4634448) (← links)
• (Q4636990) (← links)
• Greedy forward regression for variable screening (Q4639813) (← links)
• Group Regularized Estimation Under Structural Hierarchy (Q4690971) (← links)
• (Q4864293) (← links)
• Group variable selection for data with dependent structures (Q4913930) (← links)
• Variable selection for longitudinal data with high-dimensional covariates and dropouts (Q4960570) (← links)
• Model Selection via Bayesian Information Criterion for Quantile Regression Models (Q4975344) (← links)
• Interaction Screening for Ultrahigh-Dimensional Data (Q4975578) (← links)