brms 2.8.0-foss-2018b-R-3.5.1

Fit Bayesian generalized (non-)linear multivariate multilevel models using 'Stan' for full Bayesian inference. A wide range of distributions and link functions are supported, allowing users to fit - among others - linear, robust linear, count data, survival, response times, ordinal, zero-inflated, hurdle, and even self-defined mixture models all in a multilevel context. Further modeling options include non-linear and smooth terms, auto-correlation structures, censored data, meta-analytic standard errors, and quite a few more. In addition, all parameters of the response distribution can be predicted in order to perform distributional regression. Prior specifications are flexible and explicitly encourage users to apply prior distributions that actually reflect their beliefs. Model fit can easily be assessed and compared with posterior predictive checks and leave-one-out cross-validation. References: Buerkner (2017) ; Carpenter et al. (2017) .

Accessing brms 2.8.0-foss-2018b-R-3.5.1

To load the module for brms 2.8.0-foss-2018b-R-3.5.1 please use this command on the BEAR systems (BlueBEAR, BEAR Cloud VMs, and CaStLeS VMs):

module load brms/2.8.0-foss-2018b-R-3.5.1

BEAR Apps Version



  • bayesplot 1.6.0
  • brms 2.8.0
  • colourpicker 1.0
  • dygraphs
  • inline 0.3.15
  • loo 2.1.0
  • packrat 0.5.0
  • rsconnect 0.8.13
  • rstan 2.18.2
  • rstantools 1.5.1
  • shinyjs 1.0
  • shinystan 2.5.0
  • shinythemes 1.1.2
  • StanHeaders 2.18.1
  • threejs 0.3.1

More Information

For more information visit the brms website.


This version of brms has a direct dependency on: foss/2018b R/3.5.1-foss-2018b

Last modified on 3rd June 2019