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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 (≥ 0.3.3.3.0), RcppParallel (≥ 5.0.1), rstan (≥ 2.26.0), StanHeaders (≥ 2.26.0)
Suggests: bayesplot, coda, knitr, parallel, rmarkdown, testthat, viridis
Published: 2023-10-20
Author: Sean C. Anderson [aut, cre], Eric J. Ward [aut], Trustees of Columbia University [cph]
Maintainer: Sean C. Anderson <sean at seananderson.ca>
BugReports: https://github.com/seananderson/glmmfields/issues
License: GPL (≥ 3)
URL: https://github.com/seananderson/glmmfields
NeedsCompilation: yes
SystemRequirements: GNU make
Citation: glmmfields citation info
Materials: NEWS
In views: MixedModels
CRAN checks: glmmfields results

Documentation:

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

Downloads:

Package source: glmmfields_0.1.8.tar.gz
Windows binaries: r-devel: glmmfields_0.1.8.zip, r-release: glmmfields_0.1.8.zip, r-oldrel: glmmfields_0.1.8.zip
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

Linking:

Please use the canonical form https://CRAN.R-project.org/package=glmmfields to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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