Package: baytaAAR 1.0.3

Nils Müller-Scheeßel

baytaAAR: Bayesian Transition Analysis with Markov Chain Monte Carlo

Provides Bayesian age estimation for bioarchaeological skeletal data using ordinal probit regression models implemented in 'JAGS' and 'NIMBLE'. The package is designed to handle multiple ordinal traits of adult individuals and incorporates a Gompertz prior on age to reflect population-level mortality. It accounts for estimation uncertainties and supports full customization of model parameters and Markov Chain Monte Carlo settings. For more details see Müller-Scheeßel et al. (2026) <doi:10.1002/ajpa.70289>.

Authors:Nils Müller-Scheeßel [aut, cre, cph], Christoph Rinne [aut]

baytaAAR_1.0.3.tar.gz
baytaAAR_1.0.3.zip(r-4.7-any)baytaAAR_1.0.3.zip(r-4.6-any)baytaAAR_1.0.3.zip(r-4.5-any)
baytaAAR_1.0.3.tgz(r-4.6-any)baytaAAR_1.0.3.tgz(r-4.5-any)
baytaAAR_1.0.3.tar.gz(r-4.7-any)baytaAAR_1.0.3.tar.gz(r-4.6-any)
baytaAAR_1.0.3.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
baytaAAR/json (API)

# Install 'baytaAAR' in R:
install.packages('baytaAAR', repos = c('https://isaakiel.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/isaakiel/baytaaar/issues

Pkgdown/docs site:https://isaakiel.github.io

Datasets:

On CRAN:

Conda:

5.60 score 6 scripts 390 downloads 13 exports 101 dependencies

Last updated from:f4c1e3b7ab. Checks:7 NOTE, 2 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develNOTE170
source / vignettesOK359
linux-releaseNOTE182
macos-releaseNOTE171
macos-oldrelNOTE251
windows-develNOTE132
windows-releaseNOTE130
windows-oldrelNOTE94
wasm-releaseOK138

Exports:age.comp.plotage.comp.summaryage.estim.summarybay.tabay.ta.jagsbay.ta.nimblecorr.mat.meandiagnostic.summarydiagnostics.max.minprob.catsequential.binom.testthreshold.chainsthreshold.matrix

Dependencies:abindassertthatbackportsbbmlebdsmatrixbootbroomcarcarDatacheckmateclicodacolorspacecorrplotcowplotcpp11data.tableDerivdeSolvedoBydplyrevaluatefarverfastGHQuadflexsurvforecastFormulafracdiffgenericsggplot2ggpubrggrepelggsciggsignifgluegridExtragtablehighrigraphisobandknitrlabelinglatticelifecyclelme4lmtestlsodamagrittrMASSMatrixMatrixModelsmgcvminqamodelrmstatemuhazmvtnormnimblenlmenloptrnnetnumDerivpbkrtestpillarpkgconfigpolynompracmapurrrquadprogquantregR6rbibutilsRColorBrewerRcppRcppArmadilloRcppEigenRdpackreformulasrlangrstatixrstpm2S7scalesscoringRulesSparseMstatmodstringistringrsurvivaltibbletidyrtidyselecttimeDateurcautf8vctrsviridisLitewithrxfunyamlzoo

Introduction to baytaAAR
Load libraries | Introduction | Data layout | Running a first analysis | Running the analysis with JAGS | Going further | References
Rendered frombaytaAAR.Rmdusingknitr::rmarkdown

Last update: 2026-05-31
Started: 2025-09-07

Spitalfields: Comparison with known age-at-death
References
Rendered fromknown_age.Rmdusingknitr::rmarkdown

Last update: 2026-05-31
Started: 2026-04-02

Data input
Rendered fromdata_preparation.Rmdusingknitr::rmarkdown

Last update: 2026-05-29
Started: 2026-04-02

Mathematical background
Benjamin Gompertz and the Gompertz distribution | The Gompertz distribution with NIMBLE and JAGS | Mathematical notation | References
Rendered frommathematical_background.Rmdusingknitr::rmarkdown

Last update: 2026-05-07
Started: 2026-04-19

Computation framework
JAGS vs. NIMBLE vs. Stan | Parallel processing and number of chains | References
Rendered fromcomputation_framework.Rmdusingknitr::rmarkdown

Last update: 2026-05-01
Started: 2026-04-06