Post-Processing of the Markov Chain Simulated by 'ChronoModel'
or 'Oxcal'
Provides a list of functions for the statistical analysis of archaeological phases. It is based on the post-processing of the Markov Chains whose stationary distribution is the posterior distribution of a series of dates. Such MCMC output can be simulated by different applications as for instance 'ChronoModel' (see <http://www.chronomodel.fr>) or 'Oxcal' (see <https://c14.arch.ox.ac.uk/oxcal.html>). The only requirement is to have a CSV file containing a sample from the posterior distribution.
stats, utils, graphics, grDevices, hdrcde, shiny, shinythemes

Post-Processing of the Markov Chain Simulated by 'ChronoModel',
'Oxcal' or 'BCal'
Anne Philippe [aut, cre],
Marie-Anne Vibet [aut],
Thomas S. Dye [ctb]
c(
person("Anne", "Philippe", role = c("aut", "cre"), email = "anne.philippe@univ-nantes.fr"),
person("Marie-Anne", "Vibet", role = c("aut")),
person("Thomas S.", "Dye", role = c("ctb"))
)
Provides a list of functions for the statistical analysis of archaeological dates and groups of dates. It is based on the post-processing of the Markov Chains whose stationary distribution is the posterior distribution of a series of dates. Such output can be simulated by different applications as for instance 'ChronoModel' (see <http://www.chronomodel.fr>), 'Oxcal' (see <https://c14.arch.ox.ac.uk/oxcal.html>) or 'BCal' (see http://bcal.shef.ac.uk/). The only requirement is to have a csv file containing a sample from the posterior distribution.
stats, utils, graphics, grDevices, hdrcde, shiny, shinythemes,
DT, dplyr, readr, ggplot2, ggthemes

Provides a list of functions for the statistical analysis of archaeological dates and groups of dates. It is based on the post-processing of the Markov Chains whose stationary distribution is the posterior distribution of a series of dates. Such output can be simulated by different applications as for instance 'ChronoModel' (see <http://www.chronomodel.fr>), 'Oxcal' (see <https://c14.arch.ox.ac.uk/oxcal.html>) or 'BCal' (see <http://bcal.shef.ac.uk/>). The only requirement is to have a csv file containing a sample from the posterior distribution.
stats, utils, graphics, grDevices, shiny, shinythemes, DT,
readr, ggthemes, toOrdinal, ggplot2, ggalt