Research map / Probabilistic and scientific modeling / Uncertainty and Gaussian processes
Robust Inference for High-Dimensional Linear Models via Residual Randomization
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use residual randomization with the proposed selection of M | High-dimensional Lasso-based inference · Simulation settings with n = 50, p = 100 | empirical coverage | Helped |
| Use residual randomization with the proposed selection of M | High-dimensional Lasso-based inference · Simulation settings with n = 100, p = 300 | empirical coverage | Mixed |
| Use residual randomization | High-dimensional Lasso-based inference · Simulation settings | confidence interval length | Hurt |
| Increase δ when selecting M | RR · Simulation settings | empirical coverage | Helped |
| Increase δ when selecting M | RR · Simulation settings | confidence interval length | Hurt |
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