mgcv 1.9-1-foss-2022b-R-4.3.1

Generalized additive (mixed) models, some of their extensions and other generalized ridge regression with multiple smoothing parameter estimation by (Restricted) Marginal Likelihood, Generalized Cross Validation and similar, or using iterated nested Laplace approximation for fully Bayesian inference. See Wood (2017) for an overview. Includes a gam() function, a wide variety of smoothers, 'JAGS' support and distributions beyond the exponential family.

Accessing mgcv 1.9-1-foss-2022b-R-4.3.1

To load the module for mgcv 1.9-1-foss-2022b-R-4.3.1 please use this command on the BEAR systems (BlueBEAR and BEAR Cloud VMs):

📋 module load bear-apps/2022b module load mgcv/1.9-1-foss-2022b-R-4.3.1

BEAR Apps Version

2022b

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

mgcv-1.9-1

More Information

For more information visit the mgcv website.

Dependencies

This version of mgcv has a direct dependency on: foss/2022b R/4.3.1-foss-2022b

Last modified on 27th February 2024