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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: 0.2.1
Depends: R (≥ 3.5.0), nimble (≥ 0.12.0)
Imports: stats, coda, graphics
Suggests: knitr, rmarkdown
Published: 2024-08-19
DOI: 10.32614/CRAN.package.baorista
Author: Enrico Crema ORCID iD [aut, cre]
Maintainer: Enrico Crema <enrico.crema at gmail.com>
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

Documentation:

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

Downloads:

Package source: baorista_0.2.1.tar.gz
Windows binaries: r-devel: baorista_0.2.1.zip, r-release: baorista_0.2.1.zip, r-oldrel: baorista_0.2.1.zip
macOS binaries: r-release (arm64): baorista_0.2.1.tgz, r-oldrel (arm64): baorista_0.2.1.tgz, r-release (x86_64): baorista_0.2.1.tgz, r-oldrel (x86_64): baorista_0.2.1.tgz
Old sources: baorista archive

Linking:

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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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