PReMiuM 3.2.3-foss-2020a-R-4.0.0

Bayesian clustering using a Dirichlet process mixture model. This model is an alternative to regression models, non-parametrically linking a response vector to covariate data through cluster membership.

Accessing PReMiuM 3.2.3-foss-2020a-R-4.0.0

To load the module for PReMiuM 3.2.3-foss-2020a-R-4.0.0 please use this command on the BEAR systems (BlueBEAR, BEARCloud VMs, and CaStLeS VMs):

module load PReMiuM/3.2.3-foss-2020a-R-4.0.0

BEAR Apps Version




The listed architectures consist of two part: OS-CPU.

  • BlueBEAR: The OS used on BlueBEAR is represented by EL and there are several different processor (CPU) types available on BlueBEAR. More information about the processor types on BlueBEAR is available on the BlueBEAR Job Submission page.
  • BEAR and CaStLeS Cloud VMs: These VMs can have one of two OSes. Those with access to a BEAR Cloud or CaStLeS VM should check that the listed architectures for an application include the OS of VM being used. The VMs, irrespective of OS, will use the haswell CPU type.


  • PReMiuM 3.2.3

More Information

For more information visit the PReMiuM website.


This version of PReMiuM has a direct dependency on: ald/1.2-foss-2020a-R-4.0.0 foss/2020a R/4.0.0-foss-2020a rgdal/1.5-16-foss-2020a-R-4.0.0 spdep/1.1-5-foss-2020a-R-4.0.0-Python-3.8.2

Last modified on 23rd March 2021