| aenet | Adaptive Elastic-Net | 
| amnet | Adaptive MCP-Net | 
| asnet | Adaptive SCAD-Net | 
| coef.msaenet | Extract Model Coefficients | 
| msaenet | Multi-Step Adaptive Elastic-Net | 
| msaenet.fn | Get the Number of False Negative Selections | 
| msaenet.fp | Get the Number of False Positive Selections | 
| msaenet.mae | Mean Absolute Error (MAE) | 
| msaenet.mse | Mean Squared Error (MSE) | 
| msaenet.nzv | Get Indices of Non-Zero Variables | 
| msaenet.nzv.all | Get Indices of Non-Zero Variables in All Steps | 
| msaenet-package | msaenet: Multi-Step Adaptive Estimation Methods for Sparse... | 
| msaenet.rmse | Root Mean Squared Error (RMSE) | 
| msaenet.rmsle | Root Mean Squared Logarithmic Error (RMSLE) | 
| msaenet.sim.binomial | Generate Simulation Data for Benchmarking Sparse Regressions... | 
| msaenet.sim.cox | Generate Simulation Data for Benchmarking Sparse Regressions... | 
| msaenet.sim.gaussian | Generate Simulation Data for Benchmarking Sparse Regressions... | 
| msaenet.sim.poisson | Generate Simulation Data for Benchmarking Sparse Regressions... | 
| msaenet.tp | Get the Number of True Positive Selections | 
| msaenet.tune.glmnet | Automatic (parallel) parameter tuning for glmnet models | 
| msaenet.tune.ncvreg | Automatic (parallel) parameter tuning for ncvreg models | 
| msaenet.tune.nsteps.glmnet | Select the number of adaptive estimation steps | 
| msaenet.tune.nsteps.ncvreg | Select the number of adaptive estimation steps | 
| msamnet | Multi-Step Adaptive MCP-Net | 
| msasnet | Multi-Step Adaptive SCAD-Net | 
| plot.msaenet | Plot msaenet Model Objects | 
| predict.msaenet | Make Predictions from an msaenet Model | 
| print.msaenet | Print msaenet Model Information | 
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