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Gibbs Samplers for Discrete Bayesian Spatiotemporal Models

v1.1.4 · Jan 30, 2026 · GPL (>= 3)

Description

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 MolliƩ (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-MolliƩ CAR model" <doi:10.1016/j.sste.2021.100420>.

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NOTE r-oldrel-macos-arm64

installed package size

  installed size is  9.2Mb
  sub-directories of 1Mb or more:
    libs   7.0Mb
NOTE r-oldrel-macos-x86_64

installed package size

  installed size is  9.3Mb
  sub-directories of 1Mb or more:
    libs   7.0Mb
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Check History

NOTE 12 OK · 2 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE Mar 9, 2026
NOTE r-oldrel-macos-arm64

installed package size

  installed size is  9.2Mb
  sub-directories of 1Mb or more:
    libs   7.0Mb
NOTE r-oldrel-macos-x86_64

installed package size

  installed size is  9.3Mb
  sub-directories of 1Mb or more:
    libs   7.0Mb

Dependency Network

Dependencies Reverse dependencies abind matrixStats spdep RSTr

Version History

new 1.1.4 Mar 9, 2026