github paul-buerkner/brms v1.9.0
brms 1.9.0

latest releases: v2.21.0, v2.20.3, v2.19.0...
6 years ago

new features

  • Perform model comparisons based on marginal likelihoods using the methods bridge_sampler, bayes_factor, and post_prob all powered by the bridgesampling package.
  • Compute a Bayesian version of R-squared with the bayes_R2 method.
  • Specify non-linear models for all distributional parameters.
  • Combine multiple model formulas using the + operator and the helper functions lf, nlf, and set_nl.
  • Combine multiple priors using the + operator.
  • Split the nlpar argument of set_prior into the three arguments resp, dpar, and nlpar to allow for more flexible prior specifications.

other changes

  • Refactor parts of the package to prepare for the implementation of more flexible multivariate models in future updates.
  • Keep all constants in the log-posterior in order for bridge_sampler to be working correctly.
  • Reduce the amount of renaming done within the stanfit object.
  • Rename argument auxpar of fitted.brmsfit to dpar.
  • Use the launch_shinystan generic provided by the shinystan package.
  • Set bayesplot::theme_default() as the default ggplot2 theme when attaching brms.
  • Include citations of the brms overview paper as published in the Journal of Statistical Software.

bug fixes

  • Fix problems when calling fitted with hurdle_lognormal models thanks to Meghna Krishnadas.
  • Fix problems when predicting sigma in asym_laplace models thanks to Anna Josefine Sorensen.

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