paul-buerkner/brms v1.7.0 on GitHub

new features

Fit latent Gaussian processes of one
or more covariates via function gp
specified in the model formula (#221).
Rework methods fixef, ranef,
coef, and VarCorr to be more flexible
and consistent with other post-processing methods (#200).
Generalize method hypothesis to be
applicable on all objects coercible to a
data.frame (#198).
Visualize predictions via spaghetti
plots using argument spaghetti in
marginal_effects and marginal_smooths.
Introduce method add_ic to
store and reuse information criteria in
fitted model objects (#220).
Allow for negative weights in
multi-membership grouping structures.
Introduce an as.array method
for brmsfit objects.

Show output of R code in HTML vignettes thanks
to Ben Goodrich (#158).
Resolve citations in PDF vignettes thanks
to Thomas Kluth (#223).
Improve sampling efficiency for
exgaussian models thanks to
Alex Forrence (#222).
Also transform data points when using argument
transform in marginal_effects
thanks to Markus Gesmann.

Fix an unexpected error in marginal_effects
occuring for some models with autocorrelation terms
thanks to Markus Gesmann.
Fix multiple problems occuring for models with
the cor_bsts structure thanks to Andrew Ellis.