Changes in version 1.0.7                        

*** IMPORTANT: summary(object) reported the incorrect variational mean
of q(Sigma_j) [variance components]. This has been fixed; nothing
changes in estimation and object$cov has always extracted the correct
variational distribution of q(Sigma_j). Thank you to Ruggero Bellio for
bringing this to my attention.

** Added convergence criterion using "relative" ELBO, i.e. stopping when
ELBO/N increases by a small amount where N is the number of
observations.

** Adjustments to "print", e.g. only showing change in q(alpha,beta) at
convergence

  - Small adjustments to sparse matrix algebra to improve speed in
    problems with high-dimensional REs. Thank you to Ruggero Bellio and
    Hanna Niwinska for finding datasets that illustrate this problem.

  - Updates to README to reference new papers and experimental package
    branches.

  - Address certain warnings raised by Matrix-package updates.

                 Changes in version 1.0.6 (2024-11-07)                  

  - 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

                 Changes in version 1.0.5 (2024-09-12)                  

** 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.

                        Changes in version 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.

                 Changes in version 1.0.3 (2022-10-27)                  

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

                 Changes in version 1.0.2 (2022-09-23)                  

  - 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.

                 Changes in version 1.0.1 (2022-09-17)                  

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

                 Changes in version 1.0.0 (2022-09-14)                  

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