R: Self-Validated Ensemble Models with Lasso and Relaxed Elastic Net Regression

# Self-Validated Ensemble Models with Lasso and Relaxed Elastic Net Regression

## Documentation for package ‘SVEMnet’ version 3.2.1

- DESCRIPTION file.
- Package NEWS.

## Help Pages

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_prepare | Prepare data to match a 'bigexp_spec'
bigexp_terms | Create a deterministic expansion spec for wide polynomial and interaction models
bigexp_train | Build a spec and prepare training data in one call
coef.svem_model | Coefficients for SVEM Models
glmnet_with_cv | Fit a glmnet Model with Repeated Cross-Validation
lipid_screen | Lipid formulation screening data
plot.svem_binomial | Plot Method for SVEM Binomial Models
plot.svem_model | Plot Method for SVEM Models (Gaussian / Generic)
plot.svem_significance_test | Plot SVEM significance test results for one or more responses
predict.svem_cv | Predict from glmnet_with_cv Fits (svem_cv Objects)
predict.svem_model | Predict Method for SVEM Models (Gaussian and Binomial)
predict_cv | Predict from glmnet_with_cv Fits (svem_cv Objects)
print.bigexp_spec | Print method for bigexp_spec objects
print.svem_significance_test | Print Method for SVEM Significance Test
SVEMnet | Fit an SVEMnet model (Self-Validated Ensemble Elastic Net)
svem_export_candidates_csv | Export SVEM candidate sets to CSV
svem_nonzero | Coefficient Nonzero Percentages (SVEM)
svem_random_table_multi | Generate a Random Prediction Table from Multiple SVEMnet Models (no refit)
svem_score_random | Random-search scoring for SVEM models
svem_select_from_score_table | Select best row and diverse candidates from an SVEM score table
svem_significance_test_parallel | SVEM whole-model significance test with mixture support (parallel)
svem_wmt_multi | Whole-model tests for multiple SVEM responses (WMT wrapper)
with_bigexp_contrasts | Evaluate code with the spec's recorded contrast options