Implements an objective Bayes intrinsic conditional autoregressive prior. This model provides an objective Bayesian approach for modeling spatially correlated areal data using an intrinsic conditional autoregressive prior on a vector of spatial random effects.
| Version: | 1.0 |
| Depends: | R (≥ 3.1.0) |
| Imports: | rgdal, spdep, mvtnorm, coda, MCMCglmm, Rdpack, graphics |
| Suggests: | maptools, maps, MASS, sp, knitr, rmarkdown, RColorBrewer, captioner, rcrossref |
| Published: | 2018-11-19 |
| Author: | Erica M. Porter, Matthew J. Keefe, Christopher T. Franck, and Marco A.R. Ferreira |
| Maintainer: | Erica M. Porter <ericamp at vt.edu> |
| License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| NeedsCompilation: | no |
| CRAN checks: | ref.ICAR results |
| Reference manual: | ref.ICAR.pdf |
| Vignettes: |
Applying an ICAR reference prior |
| Package source: | ref.ICAR_1.0.tar.gz |
| Windows binaries: | r-devel: ref.ICAR_1.0.zip, r-release: ref.ICAR_1.0.zip, r-oldrel: ref.ICAR_1.0.zip |
| macOS binaries: | r-release: ref.ICAR_1.0.tgz, r-oldrel: ref.ICAR_1.0.tgz |
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