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 37 items.

• Solving constrained nonsmooth group sparse optimization via group Capped-\(\ell_1\) relaxation and group smoothing proximal gradient algorithm (Q6043130) (← links)
• Grouped variable selection with discrete optimization: computational and statistical perspectives (Q6046300) (← links)
• Dummy endogenous treatment effect estimation using high‐dimensional instrumental variables (Q6059396) (← links)
• Variance estimation in high-dimensional linear regression via adaptive elastic-net (Q6065189) (← links)
• Globally Adaptive Longitudinal Quantile Regression With High Dimensional Compositional Covariates (Q6069869) (← links)
• (Q6073210) (← links)
• Inferences for extended partially linear single-index models (Q6075569) (← links)
• On Joint Estimation of Gaussian Graphical Models for Spatial and Temporal Data (Q6079972) (← links)
• A nonconvex nonsmooth image prior based on the hyperbolic tangent function (Q6084629) (← links)
• Communication-efficient estimation for distributed subset selection (Q6089198) (← links)
• Quantile forward regression for high-dimensional survival data (Q6092305) (← links)
• Controlling False Discovery Rate Using Gaussian Mirrors (Q6107203) (← links)
• Honest Confidence Sets for High-Dimensional Regression by Projection and Shrinkage (Q6107222) (← links)
• Moderate-Dimensional Inferences on Quadratic Functionals in Ordinary Least Squares (Q6110712) (← links)
• Debiasing convex regularized estimators and interval estimation in linear models (Q6117025) (← links)
• Generalized matrix decomposition regression: estimation and inference for two-way structured data (Q6138615) (← links)
• Post-selection Inference of High-dimensional Logistic Regression Under Case–Control Design (Q6149873) (← links)
• Forward-selected panel data approach for program evaluation (Q6163247) (← links)
• A quadratic upper bound algorithm for regression analysis of credit risk under the proportional hazards model with case-cohort data (Q6173558) (← links)
• Improving the accuracy and internal consistency of regression-based clustering of high-dimensional datasets (Q6177168) (← links)
• A nonlinear mixed–integer programming approach for variable selection in linear regression model (Q6181891) (← links)
• Culling the Herd of Moments with Penalized Empirical Likelihood (Q6190692) (← links)
• Homogeneity and Sparsity Analysis for High-Dimensional Panel Data Models (Q6190753) (← links)
• A joint estimation for the high-dimensional regression modeling on stratified data (Q6204973) (← links)
• MuSP: a multistep screening procedure for sparse recovery (Q6541761) (← links)
• Feature grouping and sparse principal component analysis with truncated regularization (Q6548777) (← links)
• A randomized sparse Kaczmarz solver for sparse signal recovery via minimax-concave penalty (Q6559997) (← links)
• Sparse Convoluted Rank Regression in High Dimensions (Q6567944) (← links)
• Stabilized direct learning for efficient estimation of individualized treatment rules (Q6589221) (← links)
• Iterative adaptive robust variable selection in nomparametric additive models (Q6592367) (← links)
• An overview of reciprocal \(L_1\)-regularization for high dimensional regression data (Q6602178) (← links)
• Variable selection using \(L_q\) penalties (Q6604398) (← links)
• Incorporating Graphical Structure of Predictors in Sparse Quantile Regression (Q6617798) (← links)
• Inference in Additively Separable Models With a High-Dimensional Set of Conditioning Variables (Q6617817) (← links)
• One-step regularized estimator for high-dimensional regression models (Q6621326) (← links)
• Optimized variable selection via repeated data splitting (Q6627418) (← links)
• Bayesian Stein-type shrinkage estimators in high-dimensional linear regression models (Q6656180) (← links)