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

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Documentation for package ‘SVEMnet’ version 3.2.0

• 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