Multi-Step Adaptive Estimation Methods for Sparse Regressions
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Documentation for package ‘msaenet’ version 3.1.1
Help Pages
| 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.rmse | Root Mean Squared Error (RMSE) |
| msaenet.rmsle | Root Mean Squared Logarithmic Error (RMSLE) |
| msaenet.sim.binomial | Generate Simulation Data for Benchmarking Sparse Regressions (Binomial Response) |
| msaenet.sim.cox | Generate Simulation Data for Benchmarking Sparse Regressions (Cox Model) |
| msaenet.sim.gaussian | Generate Simulation Data for Benchmarking Sparse Regressions (Gaussian Response) |
| msaenet.sim.poisson | Generate Simulation Data for Benchmarking Sparse Regressions (Poisson Response) |
| msaenet.tp | Get the Number of True Positive Selections |
| 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 |