Package: SpatGC 0.1.0

SpatGC: Bayesian Modeling of Spatial Count Data

Provides a collection of functions for preparing data and fitting Bayesian count spatial regression models, with a specific focus on the Gamma-Count (GC) model. The GC model is well-suited for modeling dispersed count data, including under-dispersed or over-dispersed counts, or counts with equivalent dispersion, using Integrated Nested Laplace Approximations (INLA). The package includes functions for generating data from the GC model, as well as spatially correlated versions of the model. See Nadifar, Baghishani, Fallah (2023) <doi:10.1007/s13253-023-00550-5>.

Authors:Mahsa Nadifar [aut, cre], Hossein Baghishani [aut]

SpatGC_0.1.0.tar.gz
SpatGC_0.1.0.zip(r-4.7)SpatGC_0.1.0.zip(r-4.6)SpatGC_0.1.0.zip(r-4.5)
SpatGC_0.1.0.tgz(r-4.6-any)SpatGC_0.1.0.tgz(r-4.5-any)
SpatGC_0.1.0.tar.gz(r-4.7-any)SpatGC_0.1.0.tar.gz(r-4.6-any)
SpatGC_0.1.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html
card.svg |card.png
SpatGC/json (API)
NEWS

# Install 'SpatGC' in R:
install.packages('SpatGC', repos = c('https://mahsanst.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/mahsanst/spatgc/issues

On CRAN:

Conda:

2.70 score 152 downloads 14 exports 19 dependencies

Last updated from:6e80132935. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK146
source / vignettesOK164
linux-release-x86_64OK129
macos-release-arm64OK141
macos-oldrel-arm64OK195
windows-develOK87
windows-releaseOK106
windows-oldrelOK110
wasm-releaseOK115

Exports:dGCGGClatNBlatpGCPoislatqGCrAdjrGCrGCgeorGClatspatCARspatGEOspatICAR

Dependencies:bootclassclassIntDBIdeldire1071KernSmoothlatticeMASSmvtnormproxyRcpps2sfspspDataspdepunitswk