Package: geostan 0.8.2

geostan: Bayesian Spatial Analysis

For spatial data analysis; provides exploratory spatial analysis tools, spatial regression, spatial econometric, and 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 monitoring 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>.

Authors:Connor Donegan [aut, cre], Mitzi Morris [ctb], Amy Tims [ctb]

geostan_0.8.2.tar.gz
geostan_0.8.2.zip(r-4.7)geostan_0.8.2.zip(r-4.6)geostan_0.8.2.zip(r-4.5)
geostan_0.8.2.tgz(r-4.6-x86_64)geostan_0.8.2.tgz(r-4.6-arm64)geostan_0.8.2.tgz(r-4.5-x86_64)geostan_0.8.2.tgz(r-4.5-arm64)
geostan_0.8.2.tar.gz(r-4.7-arm64)geostan_0.8.2.tar.gz(r-4.7-x86_64)geostan_0.8.2.tar.gz(r-4.6-arm64)geostan_0.8.2.tar.gz(r-4.6-x86_64)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
geostan/json (API)

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

Bug tracker:https://github.com/connordonegan/geostan/issues

Pkgdown/docs site:https://connordonegan.github.io

Uses libs:
  • c++– GNU Standard C++ Library v3
Datasets:
  • sentencing - Florida state prison sentencing counts by county, 1905-1910

On CRAN:

Conda:

bayesianbayesian-inferencebayesian-statisticsepidemiologymodelingpublic-healthrspatialspatialstancpp

7.78 score 83 stars 81 scripts 373 downloads 43 exports 68 dependencies

Last updated from:0b23aee82e. Checks:11 WARNING, 1 OK, 1 FAIL. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64WARNING446
linux-devel-x86_64WARNING418
source / vignettesOK488
linux-release-arm64WARNING389
linux-release-x86_64WARNING403
macos-release-arm64WARNING263
macos-release-x86_64WARNING728
macos-oldrel-arm64WARNING355
macos-oldrel-x86_64WARNING646
windows-develWARNING438
windows-releaseWARNING466
windows-oldrelWARNING514
wasm-releaseFAIL181

Exports:apleauto_gaussiandicedgeseigen_gridexpected_mcgamma2get_shpgrhsimpactslglisalog_likmake_EVmcme_diagmoran_plotn_effn_nbsnormalposterior_predictprep_car_dataprep_car_data2prep_icar_dataprep_me_dataprep_sar_dataprep_sar_data2row_standardizese_logshape2matsim_sarsp_diagspatialspillstan_carstan_esfstan_glmstan_icarstan_sarstudent_tuniformwaic

Dependencies:abindbackportsBHbootcallrcheckmateclassclassIntclicpp11DBIdeldirdescdistributionale1071farvergenericsggplot2gluegridExtragtableinlineisobandKernSmoothlabelinglatticelifecycleloomagrittrMASSMatrixmatrixStatsnumDerivotelpillarpkgbuildpkgconfigposteriorprocessxproxypsQuickJSRR6RColorBrewerRcppRcppEigenRcppParallelrlangrstanrstantoolss2S7scalessfsignsspspDataspdepStanHeaderstensorAtibbletruncnormunitsutf8vctrsviridisLitewithrwk

Custom spatial models with RStan and geostan
CAR models | Autonormal model | Hierarchical model | Zero-mean parameterization | SAR models | References
Rendered fromcustom-spatial-models.Rmdusingknitr::rmarkdown

Last update: 2025-07-18
Started: 2023-10-04

Raster regression
Demonstration | Discussion | Simulating spatial data | References
Rendered fromraster-regression.Rmdusingknitr::rmarkdown

Last update: 2024-12-04
Started: 2023-05-01

Spatial analysis with geostan
Summary | Installation | From github | From CRAN | Getting started | Adjacency matrix | Non-spatial regression | MCMC output | Methods | Spatial regression | A filtering approach | A bivariate model | Predicted values | Future work and support | Appendix | References
Rendered fromspatial-analysis.Rmdusingknitr::rmarkdown

Last update: 2024-11-21
Started: 2024-10-31

Exploratory spatial data analysis
Getting started | Exploratory spatial data analysis (ESDA) | Spatial diagnostic summary | Spatial weights matrix | The Moran scatter plot | The Moran coefficient (MC) | The Geary ratio (GR) | Local indicators of spatial association (LISAs) | Effective sample size | Model diagnostics | References
Rendered frommeasuring-sa.Rmdusingknitr::rmarkdown

Last update: 2024-11-16
Started: 2021-01-06

Spatial measurement error models
Modeling errors of observation | Discussion | Getting started | Preparing the data | Spatial ME model | Visual diagnostics | Working with MCMC samples from ME models | Non-spatial ME models | Multiple covariates | Log transforms | References
Rendered fromspatial-me-models.Rmdusingknitr::rmarkdown

Last update: 2024-11-16
Started: 2021-09-14

Spatial weights matrix
Getting started | Contiguity | Visualizing connectivity | K-nearest neighbors | Row-standardized matrix | Editing the matrix | Using the matrix
Rendered fromspatial-weights-matrix.Rmdusingknitr::rmarkdown

Last update: 2024-06-02
Started: 2024-05-09