Crandore Hub

glmmfields

Generalized Linear Mixed Models with Robust Random Fields for Spatiotemporal Modeling

Implements Bayesian spatial and spatiotemporal models that optionally allow for extreme spatial deviations through time. 'glmmfields' uses a predictive process approach with random fields implemented through a multivariate-t distribution instead of the usual multivariate normal. Sampling is conducted with 'Stan'. References: Anderson and Ward (2019) <doi:10.1002/ecy.2403>.

Versions across snapshots

VersionRepositoryFileSize
0.1.8 rolling source/ R- glmmfields_0.1.8.tar.gz 340.2 KiB
0.1.8 rolling linux/jammy R-4.5 glmmfields_0.1.8.tar.gz 1.2 MiB
0.1.8 rolling linux/noble R-4.5 glmmfields_0.1.8.tar.gz 1.2 MiB
0.1.8 latest source/ R- glmmfields_0.1.8.tar.gz 340.2 KiB
0.1.8 latest linux/jammy R-4.5 glmmfields_0.1.8.tar.gz 1.2 MiB
0.1.8 latest linux/noble R-4.5 glmmfields_0.1.8.tar.gz 1.2 MiB
0.1.8 2026-04-23 source/ R- glmmfields_0.1.8.tar.gz 340.2 KiB
0.1.8 2026-04-09 windows/windows R-4.5 glmmfields_0.1.8.zip 1.5 MiB
0.1.8 2025-04-20 source/ R- glmmfields_0.1.8.tar.gz 340.2 KiB

Dependencies (latest)

Depends

Imports

LinkingTo

Suggests