Skip to contents

Takes Poisson or Binomial discrete spatial data and runs a Gibbs sampler for a variety of Spatiotemporal Conditional Autoregressive (CAR) models. Includes measures to prevent estimate over-smoothing through a restriction of model informativeness for select models. Also provides tools to load output and get median estimates. Implements methods from Besag, York, and Mollié (1991) "Bayesian image restoration, with two applications in spatial statistics" \doi{10.1007/BF00116466}, Gelfand and Vounatsou (2003) "Proper multivariate conditional autoregressive models for spatial data analysis" doi:10.1093/biostatistics/4.1.11, Quick et al. (2017) "Multivariate spatiotemporal modeling of age-specific stroke mortality" doi:10.1214/17-AOAS1068, and Quick et al. (2021) "Evaluating the informativeness of the Besag-York-Mollié CAR model" doi:10.1016/j.sste.2021.100420.

Details

The RSTr package uses Bayesian spatiotemporal modeling to spatially smooths discrete small-area event rates using information from neighboring spatial regions. See `browseVignettes("RSTr")` for a series of tutorials on basic usage of the RSTr functions.

Author

David DeLara [aut, cre] (ORCID: <https://orcid.org/0000-0003-0485-7549>), Centers for Disease Control and Prevention [aut, cph] (https://ror.org/042twtr12)

Maintainer: David DeLara <sfq1@cdc.gov>

References

Besag, J., York, J., and Mollié, A. (1991). Bayesian Image Restoration with Two Applications in Spatial Statistics (with Discussion). Annals of the Institute of Statistical Mathematics, 43, 1–59. doi:10.1007/BF00116466

Gelfand, A. E., & Vounatsou, P. (2003). Proper multivariate conditional autoregressive models for spatial data analysis. Biostatistics, 4(1), 11–25. doi:10.1093/biostatistics/4.1.11

Quick, et al. (2017). Multivariate spatiotemporal modeling of age-specific stroke mortality. Annals of Applied Statistics, 11(4), 2165–2177. doi:10.1214/17-AOAS1068

Quick, et al. (2021). Evaluating the informativeness of the Besag-York-Mollié CAR model. Spatial and Spatio-temporal Epidemiology, 37, 100420. doi:10.1016/j.sste.2021.100420