Post-Processing of Markov Chain Monte Carlo Simulations for Chronological Modelling
Activity Plot
Activity
Age-Depth Model
Data for an Analytic Graphic
Analyze Composite Allen Relations
Complement of an Allen Relation
Composition of Allen Relations
Converse of an Allen Relation
Count Allen Relations
Data for an Illustrative Graphic
Illustrate Basic and Composite Allen Relations
Intersection of Allen Relations
Joint Concurrence of Two or More Observed Intervals
Observed Frequency of an Allen Set
Observe the Relation Between two Phases
Make a Single Plot of a Nökel Lattice.
Relate Two or More Observed Intervals
The Basic Allen Relation Set
Allen Relation Between Definite Intervals
Table of Allen Relations
Union of Allen Relations
Defunct Functions in ArchaeoPhases
Deprecated Functions in ArchaeoPhases
ArchaeoPhases: Post-Processing of Markov Chain Monte Carlo Simulations...
Coerce to Coda
Coerce to Events
Coerce to Phases
Combine two MCMC Objects
Phase Time Range
Age-Depth Modeling
Check for an Original MCMC File
Cumulative Events
Coerce to a Data Frame
Phase Duration
MCMC Duration
Elapsed Time Scale
MCMC Events
Hiatus Between Two Dates
Interpolate Between Two Dates
Bayesian Credible Interval
Bayesian HPD Regions
MCMC
The Names of an Object
Occurrence Plot
Occurrence
Bayesian Test for Anteriority/Posteriority
Compute Phases
MCMC Phases
Plot Events
Plot Phases
Read BCal Output
Read ChronoModel Output
Read OxCal Output
Sensitivity
Ordering Permutation of an MCMC Object
Sort an MCMC Object
Extract or Replace Parts of an Object
Marginal Summary Statistics for Multiple MCMC Chains
Tempo Plot
Time Range
Transition Range Between Successive Phases
Statistical analysis of archaeological dates and groups of dates. This package allows to post-process Markov Chain Monte Carlo (MCMC) simulations from 'ChronoModel' <https://chronomodel.com/>, 'Oxcal' <https://c14.arch.ox.ac.uk/oxcal.html> or 'BCal' <https://bcal.shef.ac.uk/>. It provides functions for the study of rhythms of the long term from the posterior distribution of a series of dates (tempo and activity plot). It also allows the estimation and visualization of time ranges from the posterior distribution of groups of dates (e.g. duration, transition and hiatus between successive phases) as described in Philippe and Vibet (2020) <doi:10.18637/jss.v093.c01>.
Useful links