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Package: glmmfields 0.1.8

Sean C. Anderson

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>.

Authors:Sean C. Anderson [aut, cre], Eric J. Ward [aut], Trustees of Columbia University [cph]

glmmfields_0.1.8.tar.gz
glmmfields_0.1.8.zip(r-4.7-x86_64)glmmfields_0.1.8.zip(r-4.7-arm64)glmmfields_0.1.8.zip(r-4.6-x86_64)glmmfields_0.1.8.zip(r-4.6-arm64)
glmmfields_0.1.8.tar.gz(r-4.7-arm64)glmmfields_0.1.8.tar.gz(r-4.7-x86_64)glmmfields_0.1.8.tar.gz(r-4.6-arm64)glmmfields_0.1.8.tar.gz(r-4.6-x86_64)
glmmfields_0.1.8.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
glmmfields/json (API)

# Install 'glmmfields' in R:

install.packages('glmmfields', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/seananderson/glmmfields/issues

Uses libs:

onetbb– Parallelism library for C++
c++– GNU Standard C++ Library v3

On CRAN:

onetbb cpp

2.00 score 514 downloads 1 mentions 11 exports 72 dependencies

Last updated from:af8c1571cf. Checks:10 OK. Indexed: no.

Target	Result	Time
linux-devel-arm64	OK	234
linux-devel-x86_64	OK	276
source / vignettes	OK	376
linux-release-arm64	OK	229
linux-release-x86_64	OK	297
windows-devel-arm64	OK	341
windows-devel-x86_64	OK	327
windows-release-arm64	OK	323
windows-release-x86_64	OK	252
wasm-release	OK	211

Exports:glmmfields half_t lognormal loo nbinom2 posterior_linpred posterior_predict predictive_interval sim_glmmfields student_t tidy

Dependencies:abind assertthat backports BH broom broom.mixed callr checkmate cli cluster coda codetools cpp11 desc digest distributional dplyr farver forcats furrr future generics ggplot2 globals glue gridExtra gtable inline isoband labeling lattice lifecycle listenv loo magrittr matrixStats mvtnorm nlme numDeriv otel parallelly pillar pkgbuild pkgconfig plyr posterior processx ps purrr QuickJSR R6 RColorBrewer Rcpp RcppEigen RcppParallel reshape2 rlang rstan rstantools S7 scales StanHeaders stringi stringr tensorA tibble tidyr tidyselect utf8 vctrs viridisLite withr

Spatial GLMs with glmmfields

Rendered fromspatial-glms.Rmdusingknitr::rmarkdown

Last update: 2023-03-10
Started: 2018-06-24

Help page	Topics
The 'glmmfields' package.	glmmfields-package
Format data for fitting a glmmfields model	format_data
Fit a spatiotemporal random fields GLMM	glmmfields
Lognormal family	lognormal
Return LOO information criteria	loo loo.glmmfields
Negative binomial family	nbinom2
Plot predictions from an glmmfields model	plot.glmmfields
Predict from a glmmfields model	posterior_linpred posterior_linpred.glmmfields posterior_predict posterior_predict.glmmfields predict predict.glmmfields predictive_interval predictive_interval.glmmfields
Simulate a random field with a MVT distribution	sim_glmmfields
Return a vector of parameters	stan_pars
Student-t and half-t priors	half_t student_t
Tidy model output	tidy tidy.glmmfields

Package: glmmfields 0.1.8

glmmfields: Generalized Linear Mixed Models with Robust Random Fields for Spatiotemporal Modeling

Citation

Readme and manuals

Help Manual

Usage by other packages (reverse dependencies)