new features
- compute the Watanabe-Akaike information criterion (WAIC) and leave-one-out cross-validation (LOO) using the loo package.
- provide an interface to shinystan with S3 method 'launch_shiny'.
- new functions 'get_prior' and 'set_prior' to make prior specifications easier.
- log-likelihood values and posterior predictive samples can now be calculated within R after the model has been fitted.
- make predictions based on new data using S3 method 'predict'.
- allow for customized covariance structures of grouping factors with multiple random effects.
- new S3 methods 'fitted' and 'residuals' to compute fitted values and residuals, respectively.
other changes
- arguments 'WAIC' and 'predict' are removed from function 'brm' as they are no longer necessary.
- new argument 'cluster_type' in function 'brm' allowing to choose the cluster type created by the parallel package
- remove chains that fail to initialize while sampling in parallel leaving the other chains untouched.
- redesign trace and density plots to be faster and more stable.
- S3 method 'VarCorr' now always returns covariance matrices regardless of whether correlations were estimated.
bug fixes
- fix a bug in S3 method 'hypothesis' related to the calculation of Bayes factors for point hypotheses.
- user defined covariance matrices that are not strictly positive definite for numerical reasons should now be handled correctly.
- fix minor issues with internal parameter naming.
- perform additional checking on user defined priors.