| SVEMnet-package | SVEMnet: Self-Validated Ensemble Models with Relaxed Lasso and Elastic-Net Regression |
| bigexp_formula | Construct a formula for a new response using a bigexp_spec |
| bigexp_model_matrix | Build a model matrix using the spec's stored contrasts (if present) |
| bigexp_prepare | Prepare data to match a bigexp_spec (stable expansion across datasets) |
| bigexp_terms | Create a deterministic expansion spec for wide polynomial/interaction models |
| bigexp_train | Build a spec and prepare training data in one call |
| coef.svem_model | Coefficient Nonzero Percentages from an SVEM Model |
| glmnet_with_cv | Fit a glmnet Model with Cross-Validation |
| lipid_screen | Lipid formulation screening data |
| plot.svem_model | Plot Method for SVEM Models |
| plot.svem_significance_test | Plot SVEM Significance Test Results for Multiple Responses |
| plot_svem_significance_tests | Plot SVEM Significance Test Results for Multiple Responses |
| predict.svem_cv | Predict for svem_cv objects (and convenience wrapper) |
| predict.svem_model | Predict Method for SVEM Models |
| predict_cv | Predict for svem_cv objects (and convenience wrapper) |
| predict_with_ci | Percentile Confidence Intervals for SVEM Predictions |
| print.svem_significance_test | Print Method for SVEM Significance Test |
| SVEMnet | Fit an SVEMnet Model (with optional relaxed elastic net) |
| svem_optimize_random | Random-Search Optimizer with Goals, Weights, Optional CIs, and Diverse Candidates |
| svem_random_table_multi | Generate a Random Prediction Table from Multiple SVEMnet Models (no refit) |
| svem_significance_test | SVEM Significance Test with Mixture Support |
| svem_significance_test_parallel | SVEM Significance Test with Mixture Support (Parallel Version) |
| with_bigexp_contrasts | Evaluate an expression with the spec's recorded contrast options |