PReMiuM 3.2.3-foss-2020a-R-4.0.0

Unsupported: Use of this version of PReMiuM is not supported. More information on our Applications Support and Retention Policy.

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, BEAR Cloud VMs, and CaStLeS VMs):

module load bear-apps-unsupported/handbuilt/2019
module load PReMiuM/3.2.3-foss-2020a-R-4.0.0

BEAR Apps Version

2019h

Extensions

  • PReMiuM 3.2.3

More Information

For more information visit the PReMiuM website.

Dependencies

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