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glmmfields: Generalized Linear Mixed Models with Robust Random Fields forSpatiotemporal 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
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 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.html ,glmmfields.pdf
Vignettes:Spatial GLMs with glmmfields (source,R code)

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:

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