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>.

Version: 0.1.8
Depends: methods, R (≥ 3.4.0), Rcpp (≥ 0.12.18)
Imports: assertthat, broom, broom.mixed, cluster, dplyr (≥ 0.8.0), forcats, ggplot2 (≥ 2.2.0), loo (≥ 2.0.0), mvtnorm, nlme, RcppParallel (≥ 5.0.1), reshape2, rstan (≥ 2.26.0), rstantools (≥ 2.1.1), tibble
LinkingTo: BH (≥ 1.66.0), Rcpp (≥ 0.12.8), RcppEigen (≥, RcppParallel (≥ 5.0.1), rstan (≥ 2.26.0), StanHeaders (≥ 2.26.0)
Suggests: bayesplot, coda, knitr, parallel, rmarkdown, testthat, viridis
Published: 2023-10-20
DOI: 10.32614/CRAN.package.glmmfields
Author: Sean C. Anderson [aut, cre], Eric J. Ward [aut], Trustees of Columbia University [cph]
Maintainer: Sean C. Anderson <sean at>
License: GPL (≥ 3)
NeedsCompilation: yes
SystemRequirements: GNU make
Citation: glmmfields citation info
Materials: NEWS
In views: MixedModels
CRAN checks: glmmfields results


Reference manual: glmmfields.pdf
Vignettes: Spatial GLMs with glmmfields


Package source: glmmfields_0.1.8.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): glmmfields_0.1.8.tgz, r-oldrel (arm64): glmmfields_0.1.8.tgz, r-release (x86_64): glmmfields_0.1.8.tgz, r-oldrel (x86_64): glmmfields_0.1.8.tgz
Old sources: glmmfields archive


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