BchronDensityFast function

Non-parametric phase model (faster version)

This function runs a non-parametric phase model on 14C and non-14C ages via Gaussian Mixture density estimation through the mclust package

BchronDensityFast(
  ages,
  ageSds,
  calCurves,
  pathToCalCurves = system.file("data", package = "Bchron"),
  dfs = rep(100, length(ages)),
  samples = 2000,
  G = 30
)

Arguments

• ages: A vector of ages (most likely 14C)
• ageSds: A vector of 1-sigma values for the ages given above
• calCurves: A vector of values containing either intcal20, shcal20, marine20, or normal (older calibration curves such as intcal13 are also supported). Should be the same length the number of ages supplied. Non-standard calibration curves can be used provided they are supplied in the same format as those previously mentioned and are placed in the same directory. Normal indicates a normally-distributed (non-14C) age.
• pathToCalCurves: File path to where the calibration curves are located. Defaults to the system directory where the 3 standard calibration curves are stored.
• dfs: Degrees-of-freedom values for the t-distribution associated with the calibration calculation. A large value indicates Gaussian distributions assumed for the 14C ages
• samples: Number of samples of calibrated dates required
• G: Number of Gaussian mixture components

Returns

An object of class BchronDensityRunFast with the following components: - out: The output from the run of densityMclust with the given number of mixture components

• calAges: The calibrated ages from the BchronDensity function

Details

This is a faster approximate version of BchronDensity that uses the densityMclust function to compute the Gaussian mixtures for a set of calibrated ages. The method is an approximation as it does not fit a fully Bayesian model as BchronDensity does. It is designed to be a probabilistic version of the Oxcal SUM command which takes calibrated ages and sums the probability distributions with the aim of estimating activity through age as a proxy.

Examples

# Read in some data from Sluggan Moss
data(Sluggan)

# Run the model
SlugDensFast <- with(
  Sluggan,
  BchronDensityFast(
    ages = ages,
    ageSds = ageSds,
    calCurves = calCurves
  )
)

# plot it
plot(SlugDensFast)

See Also

Bchronology, BchronCalibrate, BchronRSL, BchronDensity for a slower exact version of this function