Pages that link to "Item:Q3462376"

The following pages link to SCAD-Penalized Least Absolute Deviation Regression in High-Dimensional Models (Q3462376):

Displaying 18 items.

• The \(L_1\) penalized LAD estimator for high dimensional linear regression (Q391806) (← links)
• SCAD penalized rank regression with a diverging number of parameters (Q476249) (← links)
• Regularized estimation for the least absolute relative error models with a diverging number of covariates (Q1659468) (← links)
• Fused Lasso penalized least absolute deviation estimator for high dimensional linear regression (Q1713210) (← links)
• Multiple-try simulated annealing algorithm for global optimization (Q1721625) (← links)
• Modified SCAD penalty for constrained variable selection problems (Q1731229) (← links)
• Local Walsh-average-based estimation and variable selection for single-index models (Q2010424) (← links)
• Regularization statistical inferences for partially linear models with high dimensional endogenous covariates (Q2131977) (← links)
• Variable selection and parameter estimation via WLAD-SCAD with a diverging number of parameters (Q2398409) (← links)
• A descent method for least absolute deviation Lasso problems (Q2421445) (← links)
• Penalized LAD Regression for Single-index Models (Q2821006) (← links)
• Large sample properties of the SCAD-penalized maximum likelihood estimation on high dimen\-sions (Q2883903) (← links)
• Asymptotic oracle properties of SCAD-penalized least squares estimators (Q5324537) (← links)
• Paths Following Algorithm for Penalized Logistic Regression Using SCAD and MCP (Q5415904) (← links)
• Sparse and robust estimation with ridge minimax concave penalty (Q6092060) (← links)
• A new active zero set descent algorithm for least absolute deviation with generalized LASSO penalty (Q6101007) (← links)
• Robust Estimation Using Modified Huber’s Functions With New Tails (Q6621625) (← links)
• Generalized regression estimators with concave penalties and a comparison to lasso type estimators (Q6636373) (← links)