geostan: Bayesian Spatial Analysis

For spatial data analysis; provides exploratory spatial analysis tools, spatial regression models, disease mapping models, model diagnostics, and special methods for inference with small area survey data (e.g., the America Community Survey (ACS)) and censored population health surveillance data. Models are pre-specified using the Stan programming language, a platform for Bayesian inference using Markov chain Monte Carlo (MCMC). References: Carpenter et al. (2017) <doi:10.18637/jss.v076.i01>; Donegan (2021) <doi:10.31219/osf.io/3ey65>; Donegan (2022) <doi:10.21105/joss.04716>; Donegan, Chun and Hughes (2020) <doi:10.1016/j.spasta.2020.100450>; Donegan, Chun and Griffith (2021) <doi:10.3390/ijerph18136856>; Morris et al. (2019) <doi:10.1016/j.sste.2019.100301>.

Package details

AuthorConnor Donegan [aut, cre] (<https://orcid.org/0000-0002-9698-5443>), Mitzi Morris [ctb], Amy Tims [ctb]
MaintainerConnor Donegan <connor.donegan@gmail.com>
LicenseGPL (>= 3)
Version0.6.2
URL https://connordonegan.github.io/geostan/
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("geostan")

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geostan documentation built on June 22, 2024, 9:40 a.m.