mcd {kairos} | R Documentation |
Mean Ceramic Date
Description
Estimates the Mean Ceramic Date of an assemblage.
Usage
mcd(object, dates, ...)
## S4 method for signature 'numeric,numeric'
mcd(object, dates, calendar = CE())
## S4 method for signature 'data.frame,numeric'
mcd(object, dates, calendar = CE())
## S4 method for signature 'matrix,numeric'
mcd(object, dates, calendar = CE())
Arguments
object |
A |
dates |
A length- |
... |
Currently not used. |
calendar |
An |
Details
The Mean Ceramic Date (MCD) is a point estimate of the occupation of an archaeological site (South 1977). The MCD is estimated as the weighted mean of the date midpoints of the ceramic types (based on absolute dates or the known production interval) found in a given assemblage. The weights are the relative frequencies of the respective types in the assemblage.
A bootstrapping procedure is used to estimate the confidence interval of a given MCD. For each assemblage, a large number of new bootstrap replicates is created, with the same sample size, by resampling the original assemblage with replacement. MCDs are calculated for each replicates and upper and lower boundaries of the confidence interval associated with each MCD are then returned.
Value
A MeanDate
object.
Author(s)
N. Frerebeau
References
South, S. A. (1977). Method and Theory in Historical Archaeology. New York: Academic Press.
See Also
plot(), bootstrap(), jackknife(), simulate()
Other dating methods:
event()
,
predict_event()
Examples
## Data from Peeples and Schachner 2012
data("zuni", package = "folio")
## Set the start and end dates for each ceramic type
dates <- list(
LINO = c(600, 875), KIAT = c(850, 950), RED = c(900, 1050),
GALL = c(1025, 1125), ESC = c(1050, 1150), PUBW = c(1050, 1150),
RES = c(1000, 1200), TULA = c(1175, 1300), PINE = c(1275, 1350),
PUBR = c(1000, 1200), WING = c(1100, 1200), WIPO = c(1125, 1225),
SJ = c(1200, 1300), LSJ = c(1250, 1300), SPR = c(1250, 1300),
PINER = c(1275, 1325), HESH = c(1275, 1450), KWAK = c(1275, 1450)
)
## Calculate date midpoints
mid <- vapply(X = dates, FUN = mean, FUN.VALUE = numeric(1))
## Calculate MCD
(mc_dates <- mcd(zuni[100:125, ], dates = mid))
## Get MCD in years CE
time(mc_dates, calendar = CE())
## Plot
plot(mc_dates)
## Bootstrap resampling
boot <- bootstrap(mc_dates, n = 30)
head(boot)
## Jackknife resampling
jack <- jackknife(mc_dates)
head(jack)
## Simulation
sim <- simulate(mc_dates, nsim = 30)
plot(sim, interval = "range", pch = 16)