Man pages for msaenet
Multi-Step Adaptive Estimation Methods for Sparse Regressions
| 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 | Multi-Step Adaptive Estimation Methods for Sparse Regressions |
| 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 |
