rcarbon (version 1.5.1)

ckde: Composite Kernel Density Estimates of Radiocarbon Dates

Description

Computes a Composite Kernel Density Estimate (CKDE) from multiple sets of randomly sampled calendar dates.

Usage

ckde(x, timeRange, bw, normalised = FALSE)

Value

An object of class ckdeSPD with the following elements

• timeRange The timeRange setting used.

• res.matrix A matrix containing the KDE values with rows representing calendar dates.

Arguments

x

A simdates class object, generated using sampleDates.

timeRange

A vector of length 2 indicating the start and end date of the analysis in cal BP.

bw

Kernel bandwidth to be used.

normalised

A logical variable indicating whether the contribution of individual dates should be equal (TRUE), or weighted based on the area under the curve of non-normalised calibration (FALSE). Default is TRUE.

Details

The function computes Kernel Density Estimates using randomly sampled calendar dates contained in a simdates class object (generated using the sampledates() function). The output contains nsim KDEs, where nsim is the argument used in simulate.dates(). The resulting object can be plotted to visualise a CKDE (cf Brown 2017), and if boot was set to TRUE in sampleDates its bootstrapped variant (cf McLaughlin 2018 for a similar analysis). The shape of the CKDE is comparable to an SPD generated from non-normalised dates when the argument normalised is set to FALSE.

References

Brown, W. A. 2017. The past and future of growth rate estimation in demographic temporal frequency analysis: Biodemographic interpretability and the ascendance of dynamic growth models. Journal of Archaeological Science, 80: 96–108. DOI: https://doi.org/10.1016/j.jas.2017.02.003
McLaughlin, T. R. 2018. On Applications of Space–Time Modelling with Open-Source 14C Age Calibration. Journal of Archaeological Method and Theory. DOI https://doi.org/10.1007/s10816-018-9381-3

See Also

sampleDates

Examples

if (FALSE) {
data(emedyd)
x = calibrate(x=emedyd$CRA, errors=emedyd$Error,normalised=FALSE)
bins = binPrep(sites=emedyd$SiteName, ages=emedyd$CRA,h=50)
s = sampleDates(x,bins=bins,nsim=100,boot=FALSE)
ckdeNorm = ckde(s,timeRange=c(16000,9000),bw=100,normalised=TRUE)
plot(ckdeNorm,type='multiline',calendar='BCAD')
}