# NEWS for SVEMnet

[3.2.1]
- Maintenance release for compatibility with glmnet 5.0 while preserving compatibility with glmnet 4.1-10.
- Route glmnet algorithm-control values through per-call control lists when supported by the installed glmnet version, with legacy argument handling for older glmnet versions.
- No intentional changes to SVEM weighting, model selection, prediction, or fitted object structure.

[3.1.9]
- No longer use doRNG package in svem_significance_test_parallel.
- Added discrete numeric argument to bigexp_terms()
- Added column-type checking to bigexp_terms() to help prevent unexpected behavior (e.g. user provides a column of numbers that is cast as character)

[3.1.4]
- Add blocking argument to bigexp_terms()

[3.1.2]
- Replaced svem_optimize_random() with svem_score_random and svem_select_score_from_table. Changes to "auto" objective rule.

[2.5.4]
- Added support for family="binomial". Improvements to svem_random_table_multi() and svem_optimize_random().

[2.3.1]
- Improvements to svem_random_table_multi() and svem_optimize_random()

[2.2.4]
- Added new functions to automatically build interaction and curvature effects from list of main effects. Added a Monte Carlo optimization function. Removed wGIC objective.

[2.1.2]
- Added relaxed option to SVEMnet, default to TRUE. Default objective "auto" uses weighted BIC when the number of rows of the model matrix is <= 1.3 times the number of columns, and weighted AIC otherwise.

[1.4.0]
- Add two experimental functions allowing for whole-model testing with mixture factors.

[1.3.1]
- Code changes to handle edge cases.

[1.3.0]
- Added functions glmnet_with_cv() and predict_cv() to act as a wrapper for cv.glmnet().
- Added examples to vignette

[1.2.1]
- Corrected bug in predict() introduced in 1.1.1
- Added svem_significance_test_parallel
- Added svem_significance_test_parallel to vignette

[1.1.1]
- Changed default for `predict()` to `debias=FALSE`.
- Changed default to `objective="wAIC"` for `weight_scheme="SVEM"`.
- Added SVEMnet Vignette

[1.0.3]
- First public release.
