postPredSPD function

SPD-based Posterior Predictive Check

Generates SPDs from posterior samples.

postPredSPD(
  x,
  errors,
  calCurve,
  model,
  a,
  b,
  params,
  nsim,
  method = NULL,
  spdnormalised = TRUE,
  datenormalised = TRUE,
  ncores = 1,
  verbose = TRUE
)

Arguments

• x: a vector of observed uncalibrated radiocarbon ages.
• errors: a vector of standard deviations corresponding to each estimated radiocarbon age.
• calCurve: character string naming a calibration curve already provided with the rcarbon package (currently 'intcal20','intcal13','intcal13nhpine16','shcal20','shcal13','shcal13shkauri16',''marine13','marine20').
• model: growth model
• a: lower (earliest) limit of the distribution (in BP).
• b: upper (latest) limit of the distribution (in BP).
• params: list of vectors containing model parameters. The names attribute of each vector should match growth model parameters.
• nsim: number of SPDs to be generated. Default is the length of the parameter vectors supplied in the argument params.
• method: method for the creation of random dates from the fitted model. Either 'uncalsample' or 'calsample'.
• spdnormalised: a logical variable indicating whether the total probability mass of the SPD is normalised to sum to unity for both observed and simulated data. Default is TRUE.
• datenormalised: a logical variable indicating whether dates should be normalised to sum to unity or not. Default is TRUE.
• ncores: number of cores used for for parallel execution. Default is 1.
• verbose: a logical variable indicating whether extra information on progress should be reported. Default is TRUE.

Returns

An object of class spdppc with the following elements

• obs A data.frame containing the years (in Cal BP) and the corresponding summed probability in the observed data.
• spdmat A matrix containing the summed probability distribution of the simulated data.