Estimates the Mean Ceramic Date of an assemblage.

date_mcd(object, dates, ...) # S4 method for CountMatrix,numeric date_mcd(object, dates, errors = NULL, level = 0.95, n = 1000, ...)

object | A CountMatrix or a DateModel object. |
---|---|

dates | A |

... | Currently not used. |

errors | A |

level | A length-one |

n | A non-negative |

`date_mcd`

returns a `data.frame`

with the following
columns:

- id
An identifier to link each row to an assemblage.

- date
The Mean Ceramic Date.

- error
The error on the MCD.

- lower
The lower boundary of the confidence interval.

- upper
The upper boundary of the confidence interval.

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. Confidence interval are not estimated for assemblages
with only a single type (`NA`

s are returned).

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

Other dating:
`event`

N. Frerebeau

## Mean Ceramic Date ## Coerce the zuni dataset to an abundance (count) matrix zuni_counts <- as_count(zuni) ## Set the start and end dates for each ceramic type zuni_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 zuni_mid <- vapply(X = zuni_dates, FUN = mean, FUN.VALUE = numeric(1)) ## Calculate MCD ## (we use a bootstrapping procedure to estimate the confidence interval) zuni_mcd <- date_mcd(zuni_counts, dates = zuni_mid) head(zuni_mcd)#> date lower upper #> LZ1105 1162.5000 1160.5609 1162.630 #> LZ1103 1137.8378 1135.1952 1138.447 #> LZ1100 1154.4643 1154.2346 1157.687 #> LZ1099 1090.6250 1090.1506 1090.693 #> LZ1097 1092.1875 1087.2620 1093.679 #> LZ1096 841.0714 837.0617 844.874## Event and accumulation dates (Bellanger et al.) ## See the vignette: # \donttest{ utils::vignette("dating", package = "tabula")#> Warning: vignette ‘dating’ not found# }