Title: | Bayesian Modeling of Archaeological Chronologies |
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Description: | Provides a list of functions for the Bayesian modeling of archaeological chronologies. The Bayesian models are implemented in 'JAGS' (Plummer 2003). 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. |
Authors: | Anne Philippe [aut, cre] , Marie-Anne Vibet [aut] |
Maintainer: | Anne Philippe <[email protected]> |
License: | GPL (>= 3) |
Version: | 0.2 |
Built: | 2024-09-29 04:34:13 UTC |
Source: | https://github.com/ArchaeoStat/ArchaeoChron |
Bayesian Chronologies of Gaussian Dates
chrono_Gauss( M, s, studyPeriodMin, studyPeriodMax, refYear = NULL, numberChains = 2, numberAdapt = 10000, numberUpdate = 10000, variable.names = c("theta"), numberSample = 50000, thin = 10 )
chrono_Gauss( M, s, studyPeriodMin, studyPeriodMax, refYear = NULL, numberChains = 2, numberAdapt = 10000, numberUpdate = 10000, variable.names = c("theta"), numberSample = 50000, thin = 10 )
M |
A ['numeric'] vector of measurements. |
s |
A ['numeric'] vector of errors. |
studyPeriodMin |
A length-one ['numeric'] vector specifying the start time of the study period. |
studyPeriodMax |
A length-one ['numeric'] vector specifying the end time of the study period. |
refYear |
A ['numeric'] vector specifying the reference year. If 'NULL' (the default), AD years are expected. |
numberChains |
An ['integer'] giving the number of of parallel chains for the model (see [jags.model()]). |
numberAdapt |
An ['integer'] giving the number of iterations for adaptation (see [jags.model()]). |
numberUpdate |
An ['integer'] giving the number of iterations to update the model by. |
variable.names |
A ['character'] vector giving the names of variables to be monitored (see [coda.samples()]). |
numberSample |
An ['integer'] giving the number of iterations to monitor (see [coda.samples()]). |
thin |
An ['integer'] giving the thinning interval for monitors (see [coda.samples()]). |
An ['mcmc.list'][coda::mcmc.list()] object.
A. Philippe, M.-A. Vibet
Bayesian Chronologies of Gaussian Dates Using the Event Model
chronoEvents_Gauss( M, s, measurementsPerEvent, studyPeriodMin, studyPeriodMax, refYear = NULL, numberChains = 2, numberAdapt = 10000, numberUpdate = 10000, variable.names = c("theta"), numberSample = 50000, thin = 10 )
chronoEvents_Gauss( M, s, measurementsPerEvent, studyPeriodMin, studyPeriodMax, refYear = NULL, numberChains = 2, numberAdapt = 10000, numberUpdate = 10000, variable.names = c("theta"), numberSample = 50000, thin = 10 )
M |
A ['numeric'] vector of measurements. |
s |
A ['numeric'] vector of errors. |
measurementsPerEvent |
A ['numeric'] vector of giving the number of measurements per event. |
studyPeriodMin |
A length-one ['numeric'] vector specifying the start time of the study period. |
studyPeriodMax |
A length-one ['numeric'] vector specifying the end time of the study period. |
refYear |
A ['numeric'] vector specifying the reference year. If 'NULL' (the default), AD years are expected. |
numberChains |
An ['integer'] giving the number of of parallel chains for the model (see [jags.model()]). |
numberAdapt |
An ['integer'] giving the number of iterations for adaptation (see [jags.model()]). |
numberUpdate |
An ['integer'] giving the number of iterations to update the model by. |
variable.names |
A ['character'] vector giving the names of variables to be monitored (see [coda.samples()]). |
numberSample |
An ['integer'] giving the number of iterations to monitor (see [coda.samples()]). |
thin |
An ['integer'] giving the thinning interval for monitors (see [coda.samples()]). |
An ['mcmc.list'][coda::mcmc.list()] object.
A. Philippe, M.-A. Vibet
Bayesian Chronologies of Gaussian Dates Using Oxcal Outlier Model
chronoOutliers_Gauss( M, s, outliersIndivVariance, outliersBernouilliProba, studyPeriodMin, studyPeriodMax, refYear = NULL, numberChains = 2, numberAdapt = 10000, numberUpdate = 10000, variable.names = c("theta"), numberSample = 50000, thin = 10 )
chronoOutliers_Gauss( M, s, outliersIndivVariance, outliersBernouilliProba, studyPeriodMin, studyPeriodMax, refYear = NULL, numberChains = 2, numberAdapt = 10000, numberUpdate = 10000, variable.names = c("theta"), numberSample = 50000, thin = 10 )
M |
A ['numeric'] vector of measurements. |
s |
A ['numeric'] vector of errors. |
outliersIndivVariance |
A ['numeric'] vector. |
outliersBernouilliProba |
A ['numeric'] vector. |
studyPeriodMin |
A length-one ['numeric'] vector specifying the start time of the study period. |
studyPeriodMax |
A length-one ['numeric'] vector specifying the end time of the study period. |
refYear |
A ['numeric'] vector specifying the reference year. If 'NULL' (the default), AD years are expected. |
numberChains |
An ['integer'] giving the number of of parallel chains for the model (see [jags.model()]). |
numberAdapt |
An ['integer'] giving the number of iterations for adaptation (see [jags.model()]). |
numberUpdate |
An ['integer'] giving the number of iterations to update the model by. |
variable.names |
A ['character'] vector giving the names of variables to be monitored (see [coda.samples()]). |
numberSample |
An ['integer'] giving the number of iterations to monitor (see [coda.samples()]). |
thin |
An ['integer'] giving the thinning interval for monitors (see [coda.samples()]). |
An ['mcmc.list'][coda::mcmc.list()] object.
A. Philippe, M.-A. Vibet
Combine Gaussian Dates
combination_Gauss( M, s, studyPeriodMin, studyPeriodMax, refYear = NULL, numberChains = 2, numberAdapt = 10000, numberUpdate = 10000, variable.names = c("theta"), numberSample = 50000, thin = 10 )
combination_Gauss( M, s, studyPeriodMin, studyPeriodMax, refYear = NULL, numberChains = 2, numberAdapt = 10000, numberUpdate = 10000, variable.names = c("theta"), numberSample = 50000, thin = 10 )
M |
A ['numeric'] vector of measurements. |
s |
A ['numeric'] vector of errors. |
studyPeriodMin |
A length-one ['numeric'] vector specifying the start time of the study period. |
studyPeriodMax |
A length-one ['numeric'] vector specifying the end time of the study period. |
refYear |
A ['numeric'] vector specifying the reference year. If 'NULL' (the default), AD years are expected. |
numberChains |
An ['integer'] giving the number of of parallel chains for the model (see [jags.model()]). |
numberAdapt |
An ['integer'] giving the number of iterations for adaptation (see [jags.model()]). |
numberUpdate |
An ['integer'] giving the number of iterations to update the model by. |
variable.names |
A ['character'] vector giving the names of variables to be monitored (see [coda.samples()]). |
numberSample |
An ['integer'] giving the number of iterations to monitor (see [coda.samples()]). |
thin |
An ['integer'] giving the thinning interval for monitors (see [coda.samples()]). |
An ['mcmc.list'][coda::mcmc.list()] object.
A. Philippe, M.-A. Vibet
Combine Gaussian Dates with Outliers
combinationWithOutliers_Gauss( M, s, outliersIndivVariance, outliersBernouilliProba, studyPeriodMin, studyPeriodMax, refYear = NULL, numberChains = 2, numberAdapt = 10000, numberUpdate = 10000, variable.names = c("theta"), numberSample = 50000, thin = 10 )
combinationWithOutliers_Gauss( M, s, outliersIndivVariance, outliersBernouilliProba, studyPeriodMin, studyPeriodMax, refYear = NULL, numberChains = 2, numberAdapt = 10000, numberUpdate = 10000, variable.names = c("theta"), numberSample = 50000, thin = 10 )
M |
A ['numeric'] vector of measurements. |
s |
A ['numeric'] vector of errors. |
outliersIndivVariance |
A ['numeric'] vector. |
outliersBernouilliProba |
A ['numeric'] vector. |
studyPeriodMin |
A length-one ['numeric'] vector specifying the start time of the study period. |
studyPeriodMax |
A length-one ['numeric'] vector specifying the end time of the study period. |
refYear |
A ['numeric'] vector specifying the reference year. If 'NULL' (the default), AD years are expected. |
numberChains |
An ['integer'] giving the number of of parallel chains for the model (see [jags.model()]). |
numberAdapt |
An ['integer'] giving the number of iterations for adaptation (see [jags.model()]). |
numberUpdate |
An ['integer'] giving the number of iterations to update the model by. |
variable.names |
A ['character'] vector giving the names of variables to be monitored (see [coda.samples()]). |
numberSample |
An ['integer'] giving the number of iterations to monitor (see [coda.samples()]). |
thin |
An ['integer'] giving the thinning interval for monitors (see [coda.samples()]). |
An ['mcmc.list'][coda::mcmc.list()] object.
A. Philippe, M.-A. Vibet
Combine Gaussian Dates with a Random Effect
combinationWithRandomEffect_Gauss( M, s, studyPeriodMin, studyPeriodMax, refYear = NULL, numberChains = 2, numberAdapt = 10000, numberUpdate = 10000, variable.names = c("theta"), numberSample = 50000, thin = 10 )
combinationWithRandomEffect_Gauss( M, s, studyPeriodMin, studyPeriodMax, refYear = NULL, numberChains = 2, numberAdapt = 10000, numberUpdate = 10000, variable.names = c("theta"), numberSample = 50000, thin = 10 )
M |
A ['numeric'] vector of measurements. |
s |
A ['numeric'] vector of errors. |
studyPeriodMin |
A length-one ['numeric'] vector specifying the start time of the study period. |
studyPeriodMax |
A length-one ['numeric'] vector specifying the end time of the study period. |
refYear |
A ['numeric'] vector specifying the reference year. If 'NULL' (the default), AD years are expected. |
numberChains |
An ['integer'] giving the number of of parallel chains for the model (see [jags.model()]). |
numberAdapt |
An ['integer'] giving the number of iterations for adaptation (see [jags.model()]). |
numberUpdate |
An ['integer'] giving the number of iterations to update the model by. |
variable.names |
A ['character'] vector giving the names of variables to be monitored (see [coda.samples()]). |
numberSample |
An ['integer'] giving the number of iterations to monitor (see [coda.samples()]). |
thin |
An ['integer'] giving the thinning interval for monitors (see [coda.samples()]). |
An ['mcmc.list'][coda::mcmc.list()] object.
A. Philippe, M.-A. Vibet
Event Model for Radiocarbon Dates
eventModel_C14( M, s, studyPeriodMin, studyPeriodMax, calibCurve = "intcal13", numberChains = 2, numberAdapt = 10000, numberUpdate = 10000, variable.names = c("theta"), numberSample = 50000, thin = 10 )
eventModel_C14( M, s, studyPeriodMin, studyPeriodMax, calibCurve = "intcal13", numberChains = 2, numberAdapt = 10000, numberUpdate = 10000, variable.names = c("theta"), numberSample = 50000, thin = 10 )
M |
A ['numeric'] vector of measurements. |
s |
A ['numeric'] vector of errors. |
studyPeriodMin |
A length-one ['numeric'] vector specifying the start time of the study period. |
studyPeriodMax |
A length-one ['numeric'] vector specifying the end time of the study period. |
calibCurve |
A ['character'] string specifying the calibration curve to be used. |
numberChains |
An ['integer'] giving the number of of parallel chains for the model (see [jags.model()]). |
numberAdapt |
An ['integer'] giving the number of iterations for adaptation (see [jags.model()]). |
numberUpdate |
An ['integer'] giving the number of iterations to update the model by. |
variable.names |
A ['character'] vector giving the names of variables to be monitored (see [coda.samples()]). |
numberSample |
An ['integer'] giving the number of iterations to monitor (see [coda.samples()]). |
thin |
An ['integer'] giving the thinning interval for monitors (see [coda.samples()]). |
An ['mcmc.list'][coda::mcmc.list()] object.
A. Philippe, M.-A. Vibet
Event Model for Gaussian Dates
eventModel_Gauss( M, s, studyPeriodMin, studyPeriodMax, refYear = NULL, numberChains = 2, numberAdapt = 10000, numberUpdate = 10000, variable.names = c("theta"), numberSample = 50000, thin = 10 )
eventModel_Gauss( M, s, studyPeriodMin, studyPeriodMax, refYear = NULL, numberChains = 2, numberAdapt = 10000, numberUpdate = 10000, variable.names = c("theta"), numberSample = 50000, thin = 10 )
M |
A ['numeric'] vector of measurements. |
s |
A ['numeric'] vector of errors. |
studyPeriodMin |
A length-one ['numeric'] vector specifying the start time of the study period. |
studyPeriodMax |
A length-one ['numeric'] vector specifying the end time of the study period. |
refYear |
A ['numeric'] vector specifying the reference year. If 'NULL' (the default), AD years are expected. |
numberChains |
An ['integer'] giving the number of of parallel chains for the model (see [jags.model()]). |
numberAdapt |
An ['integer'] giving the number of iterations for adaptation (see [jags.model()]). |
numberUpdate |
An ['integer'] giving the number of iterations to update the model by. |
variable.names |
A ['character'] vector giving the names of variables to be monitored (see [coda.samples()]). |
numberSample |
An ['integer'] giving the number of iterations to monitor (see [coda.samples()]). |
thin |
An ['integer'] giving the thinning interval for monitors (see [coda.samples()]). |
An ['mcmc.list'][coda::mcmc.list()] object.
A. Philippe, M.-A. Vibet