Provides a list of functions for the Bayesian modeling of archaeological chronologies. The Bayesian models are implemented in 'JAGS' ('JAGS' stands for Just Another Gibbs Sampler. It is a program for the analysis of Bayesian hierarchical models using Markov Chain Monte Carlo (MCMC) simulation. See < http://mcmc-jags.sourceforge.net/> and "JAGS Version 4.3.0 user manual", Martin Plummer (2017) < https://sourceforge.net/projects/mcmc-jags/files/Manuals/>.). The inputs are measurements with their associated standard deviations and the study period. The output is the MCMC sample of the posterior distribution of the event date with or without radiocarbon calibration.
Initial release. ArchaeoChron provides functions that return a Markov chain of the posterior distribution of one of the following Bayesian models.
combination_Gauss() : A function for a simple combination of Gaussian dates
combinationWithOutliers_Gauss() : A function for combining Gaussian dates using the outliers model described in Bronk Ramsey, 2009.
combinationWithRandomEffect_Gauss() : A function for combining Gaussian dates introducing a random effect (Congdom, 2010)
eventModel_Gauss() : A function for combining Gaussian dates introducing an individual random effect (Lanos and Philippe, 2017)
chrono_Gauss() : A function for a simple chronology of Gaussian dates
chronoOutliers_Gauss() : A function for the chronology of Gaussian dates associated with an outlier modeling (Bronk Ramsey, 2009)
chronoEvents_Gauss() : A function for the chronology of events combining Gaussian dates (Lanos and Philippe, 2017)
eventModel_C14() : A function for combining radiocarbon dates