brms 2.4.0

New features

• Define custom variables in all of Stan's program blocks via function stanvar. (#459)
• Change the scope of non-linear parameters to be global within univariate models. (#390)
• Allow to automatically group predictor values in Gaussian processes specified via gp. This may lead to a considerable increase in sampling efficiency. (#300)
• Compute LOO-adjusted R-squared using method loo_R2.
• Compute non-linear predictors outside of a loop over observations by means of argument loop in brmsformula.
• Fit non-linear mixture models. (#456)
• Fit censored or truncated mixture models. (#469)
• Allow horseshoe and lasso priors to be set on special population-level effects.
• Allow vectors of length greater one to be passed to set_prior.
• Conveniently save and load fitted model objects in brm via argument file. (#472)
• Display posterior probabilities in the output of hypothesis.

Other changes

• Deprecate argument stan_funs in brm in favor of using the stanvars argument for the specification of custom Stan functions.
• Deprecate arguments flist and ... in nlf.
• Deprecate argument dpar in lf and nlf.

Bug fixes

• Allow custom families in mixture models thanks to Noam Ross. (#453)
• Ensure compatibility with mice version 3.0. (#455)
• Fix naming of correlation parameters of group-level terms with multiple subgroups thanks to Kristoffer Magnusson. (#457)
• Improve scaling of default priors in lognormal models (#460).
• Fix multiple problems in the post-processing of categorical models.
• Fix validation of nested grouping factors in post-processing methods when passing new data thanks to Liam Kendall.