paul-buerkner/brms v0.8.0 on GitHub

new features

Implement generalized non-linear models, which
can be specified with the help of the nonlinear
argument in brm.
Compute and plot marginal effects using the
marginal_effects method thanks to the help
of Ruben Arslan.
Implement zero-inflated beta models through
family zero_inflated_beta thanks to the
idea of Ali Roshan Ghias.
Allow to restrict domain of fixed effects and
autocorrelation parameters using new arguments
lb and ub in function set_prior
thanks to the idea of Joel Gombin.
Add an as.mcmc method for compatibility
with the coda package.
Allow to call the WAIC, LOO,
and logLik methods with new data.

Make sure that brms is fully compatible
with loo version 0.1.5.
Optionally define the intercept
as an ordinary fixed effect to avoid the
reparametrization via centering of the
fixed effects design matrix.
Do not compute the WAIC in summary
by default anymore to reduce computation time
of the method for larger models.
The cauchy family is now deprecated
and will be removed soon as it often has convergence
issues and not much practical application anyway.
Change the default settings of the number of
chains and warmup samples to the defaults of rstan
(i.e., chains = 4 and warmup = iter / 2).
Do not remove bad behaving chains anymore as
they may point to general convergence problems that
are dangerous to ignore.
Improve flexibility of the theme argument
in all plotting functions.
Only show the legend once per page, when computing
trace and density plots with the plot method.
Move code of self-defined Stan functions
to inst/chunks and incorporate them into the
models using rstan::stanc_builder.
Also, add unit tests for these functions.

Fix problems when predicting with newdata
for zero-inflated and hurdle models thanks to Ruben Arslan.
Fix problems when predicting with newdata
if it is a subset of the data stored in a
brmsfit object thanks to Ruben Arslan.
Fix data preparation for multivariate models
if some responses are NA thanks to Raphael Royaute.
Fix a bug in the predict method occurring
for some multivariate models so that it now always
returns the predictions of all response variables,
not just the first one.
Fix a bug in the log-likelihood computation of
hurdle_poisson and hurdle_negbinomial models.
This may lead to minor changes in the values obtained by
WAIC and LOO for these models.
Fix some backwards compatibility issues of models fitted
with version <= 0.5.0 thanks to Ulf Koether.