new features
- Fit models on multiple imputed datasets via
brm_multiple
thanks to Ruben Arslan. (#27) - Combine multiple
brmsfit
objects via functioncombine_models
. - Compute model averaged posterior predictions with method
pp_average
. (#319) - Add new argument
ordinal
tomarginal_effects
to generate special plots for ordinal models thanks to the idea of the GitHub user silberzwiebel. (#190) - Use informative inverse-gamma priors for length-scale parameters of Gaussian processes. (#275)
- Compute hypotheses for all levels of a grouping factor at once using argument
scope
in methodhypothesis
. (#327) - Vectorize user-defined
Stan
functions exported viaexport_functions
using argumentvectorize
. - Allow predicting new data in models with ARMA autocorrelation structures.
bug fixes
- Correctly recover noise-free coefficients through
me
terms thanks to Ruben Arslan. As a side effect, it is no longer possible to define priors on noise-freeXme
variables directly, but only on their hyper-parametersmeanme
andsdme
. - Fix problems in renaming parameters of the
cor_bsts
structure thanks to Joshua Edward Morten. (#312) - Fix some unexpected errors when predicting from ordinal models thanks to David Hervas and Florian Bader. (#306, #307, #331)
- Fix problems when estimating and predicting multivariate ordinal models thanks to David West. (#314)
- Fix various minor problems in autocorrelation structures thanks to David West. (#320)