Estimates the Mean Ceramic Date of an assemblage.

mcd(object, dates, ...)

# S4 method for CountMatrix,numeric
mcd(object, dates)

# S4 method for MeanDate
bootstrap(
  object,
  level = 0.95,
  type = c("student", "normal"),
  probs = c(0.25, 0.5, 0.75),
  n = 1000
)

# S4 method for MeanDate
jackknife(object)

Arguments

object

A arkhe::CountMatrix or a MeanDate object.

dates

A numeric vector of dates.

...

Currently not used.

level

A length-one numeric vector giving the confidence level. Must be a single number between \(0\) and \(1\). If NULL, no confidence interval are computed.

type

A character string giving the type of confidence interval to be returned. It must be one "student" (default) or "normal". Any unambiguous substring can be given. Only used if level is not NULL.``

probs

A numeric vector of probabilities with values in \([0,1]\) (see stats::quantile()). If NULL, quantiles are not computed.

n

A non-negative integer giving the number of bootstrap replications.

Value

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.

References

South, S. A. (1977). Method and Theory in Historical Archaeology. New York: Academic Press.

See also

plot_mcd

Other dating methods: event()

Author

N. Frerebeau

Examples

## Mean Ceramic Date
## Coerce the zuni dataset to an abundance (count) matrix
data("zuni", package = "folio")
counts <- as_count(zuni)

## 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(counts, dates = mid)
head(mc_dates)
#>    LZ1105    LZ1103    LZ1100    LZ1099    LZ1097    LZ1096 
#> 1162.5000 1137.8378 1154.4643 1090.6250 1092.1875  841.0714 

## Plot
plot(mc_dates, select = 100:125)


## Bootstrap resampling
boot <- bootstrap(mc_dates, n = 30)
head(boot)
#>             min      mean       max     lower     upper       Q25       Q50
#> LZ1105 1139.062 1170.1562 1198.4375 1164.0402 1176.2723 1158.2031 1171.0938
#> LZ1103 1080.068 1137.6577 1183.7838 1128.0531 1147.2623 1122.8885 1143.0743
#> LZ1100 1083.036 1148.3036 1208.0357 1137.0824 1159.5247 1130.3571 1145.0893
#> LZ1099 1084.375 1091.4583 1100.0000 1089.7540 1093.1627 1087.5000 1090.6250
#> LZ1097  956.250 1086.1458 1175.0000 1064.7641 1107.5275 1054.6875 1092.1875
#> LZ1096  737.500  834.1667  996.4286  808.9116  859.4217  789.2857  841.0714
#>              Q75
#> LZ1105 1184.3750
#> LZ1103 1155.8277
#> LZ1100 1167.1875
#> LZ1099 1093.7500
#> LZ1097 1135.5469
#> LZ1096  892.8571

## Jackknife resampling
jack <- jackknife(mc_dates)
head(jack)
#>             mean       bias     error
#> LZ1105 1162.4206  -1.349206  28.22921
#> LZ1103 1137.4923  -5.874698  68.74235
#> LZ1100 1153.8196 -10.959746  50.11661
#> LZ1099 1090.7242   1.686508  10.14794
#> LZ1097 1091.6749  -8.713624  71.14024
#> LZ1096  849.7024 146.726190 268.67089