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 and BEAR Cloud VMs):

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

BEAR Apps Version

2020a

Architectures

EL8-cascadelake — EL8-icelake — EL8-sapphirerapids

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

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