paul-buerkner/brms v1.8.0 on GitHub

new features

Fit conditional autoregressive (CAR) models
via function cor_car thanks to the case
study of Max Joseph.
Fit spatial autoregressive (SAR) models
via function cor_sar. Currently works
for families gaussian and student.
Implement skew normal models via family
skew_normal. Thanks to Stephen Martin
for suggestions on the parameterization.
Add method reloo to perform exact
cross-validation for problematic observations
and kfold to perform k-fold cross-validation
thanks to the Stan Team.
Regularize non-zero coefficients in the
horseshoe prior thanks to Juho Piironen
and Aki Vehtari.
Add argument new_objects to various
post-processing methods to allow for passing of
data objects, which cannot be passed via
newdata.
Improve parallel execution flexibility
via the future package.

Improve efficiency and stability of ARMA models.
Throw an error when the intercept is removed
in an ordinal model instead of silently adding
it back again.
Deprecate argument threshold in brm
and instead recommend passing threshold directly
to the ordinal family functions.
Throw an error instead of a message when
invalid priors are passed.
Change the default value of the autocor
slot in brmsfit objects to an empty
cor_brms object.
Shorten Stan code by combining
declarations and definitions where possible.

Fix problems in pp_check
when the variable specified in argument
x has attributes thanks to
Paul Galpern.
Fix problems when computing fitted
values for truncated discrete models based
on new data thanks to Nathan Doogan.
Fix unexpected errors when passing
models, which did not properly initiliaze,
to various post-processing methods.
Do not accidently drop the second
dimension of matrices in summary.brmsfit
for models with only a single observation.