baorista: Bayesian Aoristic Analyses

Provides an alternative approach to aoristic analyses for archaeological datasets by fitting Bayesian parametric growth models and non-parametric random-walk Intrinsic Conditional Autoregressive (ICAR) models on time frequency data (Crema (2024)<doi:10.1111/arcm.12984>). It handles event typo-chronology based timespans defined by start/end date as well as more complex user-provided vector of probabilities.

Version: 0.1.4
Depends: R (≥ 3.5.0), nimble (≥ 0.12.0)
Imports: stats, coda, graphics
Suggests: knitr, rmarkdown
Published: 2024-06-12
DOI: 10.32614/CRAN.package.baorista
Author: Enrico Crema ORCID iD [aut, cre]
Maintainer: Enrico Crema <enrico.crema at>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: no
Language: en-GB
Citation: baorista citation info
Materials: README NEWS
CRAN checks: baorista results


Reference manual: baorista.pdf
Vignettes: Quick Start with the baorista R package


Package source: baorista_0.1.4.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): baorista_0.1.4.tgz, r-oldrel (arm64): baorista_0.1.4.tgz, r-release (x86_64): baorista_0.1.4.tgz, r-oldrel (x86_64): baorista_0.1.4.tgz
Old sources: baorista archive


Please use the canonical form to link to this page.