NEWS.md

In mgoplerud/vglmer: Variational Inference for Hierarchical Generalized Linear Models

vglmer 1.0.6

• Removes unnecessary model preparation steps for parameter_expansion="translation" and factorization_method="strong". Improves speed on default settings for models with many random effects.

• Updated references in documentation.

• Small adjustment to tests to prevent failure from update to waldo package

vglmer 1.0.5

** Add gKRLS as an option for smoothing multiple (continuous) covariates. Chang and Goplerud (2024; https://doi.org/10.1017/pan.2023.27) provides more details.

vglmer 1.0.4

• Adjust predict.vglmer to allow for faster predictions on large datasets by not copying and filling in a large sparse matrix. Thank you to Michael Auslen for pointing out this issue.

• Add the option for terms to predict to allow for predictions for each random effect separately

• Address a bug where predictions with NA in new data.frame would fail for certain splines or for cases where newdata had a single row.

vglmer 1.0.3

• Adjust vglmer to not throw deprecation messages with Matrix 1.5. Thank you to Mikael Jagan for suggestions on how to adapt the code.

vglmer 1.0.2

• IMPORTANT: Fixes bug where prediction with only one spline (and no random effects) was wrong; the non-linear part of the spline was ignored.
• Smaller bug fixes around splines (e.g., for using a single knot) have been added as well as updated tests.

vglmer 1.0.1

• Patch to address compiler issues on CRAN
• Add links to GitHub to description

vglmer 1.0.0

• Initial submission to CRAN. Estimates linear, binomial, and negative binomial (experimental) models.

mgoplerud/vglmer documentation built on Jan. 22, 2025, 6:43 p.m.