paul-buerkner/brms v0.7.0 on GitHub

new features

allow to use variational inference algorithms
as alternative to the NUTS sampler by specifying
argument algorithm in the brm function
implement beta regression models through family
Beta
implement zero-inflated binomial models through family
zero_inflated_binomial
implement multiplicative effects for family
bernoulli to fit (among others) 2PL IRT models
allow to combine fixed and random effects estimates using
the new coef method
allow to call the residuals method with newdata
allow new levels of random effects grouping
factors in the predict, fitted, and residuals
methods using argument allow_new_levels
allow to selectively exclude random effects
in the predict, fitted, and residuals
methods using argument re_formula
add a plot method for objects returned by
method hypothesis to visualize prior and posterior
distributions of the hypotheses being tested

improve evaluation of the response
part of the formula argument to
reliably allow terms with more than one variable
(e.g., y/x ~ 1)
improve sampling efficiency of models containing
many fixed effects through centering the fixed effects
design matrix
improve sampling efficiency of models containing
uncorrelated random effects specified by means
of (random || group) terms in formula
utilize user-defined functions in the Stan code
of ordinal models to improve readability as well as
sampling efficiency
make sure that model comparisons using LOO
or WAIC are only performed when models are
based on the same responses
use some generic functions of the lme4
package to avoid unnecessary function masking. This
leads to a change in the argument order of
method VarCorr
allow to change the ggplot theme in the
plot method through argument theme
remove the n. prefix in arguments
n.iter, n.warmup, n.thin, n.chains,
and n.cluster of the brm function.
The old argument names remain usable as deprecated aliases
amend names of random effects parameters to simplify
matching with their respective grouping factor levels

fix a bug in the hypothesis method
that could cause valid model parameters to be falsely
reported as invalid
fix a bug in the prior_samples method
that could cause prior samples of parameters
of the same class to be artifically correlated
fix Stan code of linear models with
moving-average effects and non-identity link functions
so that they no longer contain code related solely
to autoregressive effects
fix a bug in the evaluation of formula that
could cause complicated random effects terms to be
falsely treated as fixed effects
fix several bugs when calling the fitted
and predict methods with newdata