Penalized Elastic Net S/MM-Estimator of Regression
Coordinate Descent (CD) Algorithm to Compute Penalized Elastic Net S-e...
Change the Cross-Validation Measure
Extract Coefficient Estimates
Compute the M-estimate of Location and Scale
MM-Algorithm to Compute Penalized Elastic Net S- and M-Estimates
Options for the M-scale Estimation Algorithm
Compute the Gradient and Hessian of the M-Scale Function
Compute the M-Scale of Centered Values
Cross-validation for (Adaptive) PENSE Estimates
Compute (Adaptive) Elastic Net S-Estimates of Regression
Plot Method for Penalized Estimates With Cross-Validation
Plot Method for Penalized Estimates
Run replicated K-fold CV with random splits, matching the global estim...
Run replicated K-fold CV with random splits
Standardize data
Cross-validation for Least-Squares (Adaptive) Elastic Net Estimates
Compute the Least Squares (Adaptive) Elastic Net Regularization Path
Use the ADMM Elastic Net Algorithm
Control the Algorithm to Compute (Weighted) Least-Squares Elastic Net ...
Use Coordinate Descent to Solve Elastic Net Problems
Use the DAL Elastic Net Algorithm
Use the LARS Elastic Net Algorithm
Ridge optimizer using an Augmented data matrix. Only available for Rid...
ENPY Initial Estimates for EN S-Estimators
Options for the ENPY Algorithm
Compute the M-estimate of Location
Extract Coefficient Estimates
Approximate Value Matching
Get the Constant for Consistency for the M-Scale Using the Bisquare Rh...
Get the constant for the desired efficiency of the M-estimate of locat...
Determine a breakdown point with stable numerical properties of the M-...
Get the constant for the desired efficiency of the M-estimate of locat...
Get the Constant for Consistency for the M-Scale Using the Optimal Rho...
Get the constant for the desired efficiency of the M-estimate of locat...
Predict Method for PENSE Fits
Predict Method for PENSE Fits
Prediction Performance of Adaptive PENSE Fits
Principal Sensitivity Components
Print Metrics
Cross-validation for (Adaptive) Elastic Net M-Estimates
Compute (Adaptive) Elastic Net M-Estimates of Regression
Extract Residuals
Extract Residuals
List Available Rho Functions
Get the Constant for Consistency for the M-Scale and for Efficiency fo...
Create Starting Points for the PENSE Algorithm
Summarize Cross-Validated PENSE Fit
Compute the Tau-Scale of Centered Values
Robust penalized (adaptive) elastic net S and M estimators for linear regression. The adaptive methods are proposed in Kepplinger, D. (2023) <doi:10.1016/j.csda.2023.107730> and the non-adaptive methods in Cohen Freue, G. V., Kepplinger, D., Salibián-Barrera, M., and Smucler, E. (2019) <doi:10.1214/19-AOAS1269>. The package implements robust hyper-parameter selection with robust information sharing cross-validation according to Kepplinger & Wei (2025) <doi:10.1080/00401706.2025.2540970>.
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