Robust fitting of linear regression models

Fitting and estimating prediction performance

Fit linear regression models for a set of penalization levels and estimate the prediction performance via cross-validation.

pense_cv() adapense_cv()

Cross-validation for (Adaptive) PENSE Estimates

pensem_cv()

Compute Penalized Elastic Net M-Estimates from PENSE

regmest_cv() adamest_cv()

Cross-validation for (Adaptive) Elastic Net M-Estimates

Fitting only

pense()

Compute (Adaptive) Elastic Net S-Estimates of Regression

regmest()

Compute (Adaptive) Elastic Net M-Estimates of Regression

Plotting and printing

Methods for plotting and summarizing fits.

plot(<pense_cvfit>)

Plot Method for Penalized Estimates With Cross-Validation

plot(<pense_fit>)

Plot Method for Penalized Estimates

prediction_performance() print(<pense_pred_perf>)

Prediction Performance of Adaptive PENSE Fits

summary(<pense_cvfit>) print(<pense_cvfit>)

Summarize Cross-Validated PENSE Fit

Extracting information

Methods for extracting coefficient estimates and predicting values.

coef(<pense_cvfit>)

Extract Coefficient Estimates

coef(<pense_fit>)

Extract Coefficient Estimates

predict(<pense_cvfit>)

Predict Method for PENSE Fits

predict(<pense_fit>)

Predict Method for PENSE Fits

residuals(<pense_cvfit>)

Extract Residuals

residuals(<pense_fit>)

Extract Residuals

Robust location and scale

Compute robust location and scale estimates.

mloc()

Compute the M-estimate of Location

mlocscale()

Compute the M-estimate of Location and Scale

mscale()

Compute the M-Scale of Centered Values

tau_size()

Compute the Tau-Scale of Centered Values

Non-robust methods

Non-robust methods for fitting linear regression models.

elnet()

Compute the Least Squares (Adaptive) Elastic Net Regularization Path

elnet_cv()

Cross-validation for Least-Squares (Adaptive) Elastic Net Estimates

Advanced functionality

Control options

en_options_aug_lars() en_options_dal()

Deprecated

en_admm_options()

Use the ADMM Elastic Net Algorithm

en_algorithm_options

Control the Algorithm to Compute (Weighted) Least-Squares Elastic Net Estimates

en_dal_options()

Use the DAL Elastic Net Algorithm

en_lars_options()

Use the LARS Elastic Net Algorithm

enpy_options()

Options for the ENPY Algorithm

initest_options()

Deprecated

mm_algorithm_options()

MM-Algorithm to Compute Penalized Elastic Net S- and M-Estimates

mscale_algorithm_options()

Options for the M-scale Estimation Algorithm

mstep_options()

Deprecated

pense_options()

Deprecated

Initial estimates

Manually compute and alter initial estimates.

enpy_initial_estimates()

ENPY Initial Estimates for EN S-Estimators

prinsens()

Principal Sensitivity Components

starting_point() as_starting_point()

Create Starting Points for the PENSE Algorithm

Miscellaneous

consistency_const()

Get the Constant for Consistency for the M-Scale

rho_function()

List Available Rho Functions

Deprecated functions

en_options_aug_lars() en_options_dal()

Deprecated

enpy()

Deprecated

initest_options()

Deprecated

mstep_options()

Deprecated

pense_options()

Deprecated

pensem()

Deprecated Alias of pensem_cv