VGAM 1.1-3-foss-2019b-R-3.6.2

An implementation of about 6 major classes of statistical regression models. The central algorithm is Fisher scoring and iterative reweighted least squares. At the heart of this package are the vector generalized linear and additive model (VGLM/VGAM) classes. VGLMs can be loosely thought of as multivariate GLMs. VGAMs are data-driven VGLMs that use smoothing.

Accessing VGAM 1.1-3-foss-2019b-R-3.6.2

To load the module for VGAM 1.1-3-foss-2019b-R-3.6.2 please use this command on the BEAR systems (BlueBEAR and BEAR Cloud VMs):

📋 module load VGAM/1.1-3-foss-2019b-R-3.6.2

BEAR Apps Version

2019b

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

• VGAM-1.1-3

More Information

For more information visit the VGAM website.

Dependencies

This version of VGAM has a direct dependency on: foss/2019b R/3.6.2-foss-2019b

Last modified on 21st September 2020