New features
- Fit approximate and non-isotropic Gaussian processes via
gp
. (#540) - Enable parallelization of model fitting in
brm_multiple
via the future package. (#364) - Perform posterior predictions based on k-fold cross-validation via
kfold_predict
. (#468) - Indicate observations for out-of-sample predictions in ARMA models via argument
oos
ofextract_draws
. (#539)
Other changes
- Allow factor-like variables in smooth terms. (#562)
- Make plotting of
marginal_effects
more robust to the usage of non-standard variable names. - Deactivate certain data validity checks when using custom families.
- Improve efficiency of adjacent category models.
- No longer print informational messages from the Stan parser.
Bug fixes
- Fix an issue that could result in a substantial efficiency drop of various post-processing methods for larger models.
- Fix an issue when that resulted in an error when using
fitted(..., scale = "linear")
with ordinal models thanks to Andrew Milne. (#557) - Allow setting priors on the overall intercept in sparse models.
- Allow sampling from models with only a single observation that also contain an offset thanks to Antonio Vargas. (#545)
- Fix an error when sampling from priors in mixture models thanks to Jacki Buros Novik. (#542)
- Fix a problem when trying to sample from priors of parameter transformations.
- Allow using
marginal_smooths
with ordinal models thanks to Andrew Milne. (#570) - Fix an error in the post-processing of
me
terms thanks to the GitHub user hlluik. (#571) - Correctly update
warmup
samples when usingupdate.brmsfit
.