Chronological Apportioning

Usage

apportion(object, ...)

# S4 method for class 'data.frame'
apportion(
  object,
  s0,
  s1,
  t0,
  t1,
  from = min(s0),
  to = max(s1),
  step = 25,
  method = c("uniform", "truncated"),
  z = 2,
  progress = getOption("kairos.progress")
)

# S4 method for class 'matrix'
apportion(
  object,
  s0,
  s1,
  t0,
  t1,
  from = min(s0),
  to = max(s1),
  step = 25,
  method = c("uniform", "truncated"),
  z = 2,
  progress = getOption("kairos.progress")
)

Arguments

object: A \(m \times p\) numeric matrix or data.frame of count data (absolute frequencies giving the number of individuals for each category, i.e. a contingency table). A data.frame will be coerced to a numeric matrix via data.matrix().
...: Currently not used.
s0: A length-\(m\) numeric vector giving the site beginning dates expressed in CE years (BCE years must be given as negative numbers).
s1: A length-\(m\) numeric vector giving the site end dates expressed in CE years (BCE years must be given as negative numbers).
t0: A length-\(p\) numeric vector giving the type beginning dates expressed in CE years (BCE years must be given as negative numbers).
t1: A length-\(p\) numeric vector giving the type end dates expressed in CE years (BCE years must be given as negative numbers).
from: A length-one numeric vector giving the beginning of the period of interest (in years CE).
to: A length-one numeric vector giving the end of the period of interest (in years CE).
step: A length-one integer vector giving the step size, i.e. the width of each time step for apportioning (in years CE; defaults to \(25\)).
method: A character string specifying the distribution to be used (type popularity curve). It must be one of "uniform" (uniform distribution) or "truncated" (truncated standard normal distribution). Any unambiguous substring can be given.
z: An integer value giving the lower and upper truncation points (defaults to \(2\)). Only used if method is "truncated".
progress: A logical scalar: should a progress bar be displayed?

Value

A CountApportion object.

References

Roberts, J. M., Mills, B. J., Clark, J. J., Haas, W. R., Huntley, D. L. & Trowbridge, M. A. (2012). A Method for Chronological Apportioning of Ceramic Assemblages. Journal of Archaeological Science, 39(5): 1513-20. doi:10.1016/j.jas.2011.12.022 .

Author

N. Frerebeau

Examples

## Replication of Roberts et al. 2012
bayless <- matrix(
  data = c(4, 333, 11, 11, 13, 1605, 252, 9, 48), nrow = 1,
  dimnames = list(c("Bayless"), c("CWW", "CBW", "LMGRW", "LTB", "MMS",
                                  "PBW", "RRW", "SCBW", "TBBW"))
)

## Set ware start and end dates
start <- c(550, 800, 1200, 1150, 1275, 200, 1275, 1200, 750)
end <- c(1325, 1400, 1450, 1300, 1400, 1450, 1450, 1450, 1300)

## Apportion ceramic assemblage under flat/uniform distribution
app <- apportion(bayless, s0 = 1200, s1 = 1350, t0 = start, t1 = end,
                 step = 50, method = "uniform")

## Apportion ceramic assemblage under truncated standard normal distribution
app <- apportion(bayless, s0 = 1200, s1 = 1350, t0 = start, t1 = end,
                 step = 50, method = "truncated", z = 2)

## Array of results
head(app)
#> , , 1200_1250
#> 
#>              CWW      CBW    LMGRW      LTB MMS     PBW RRW     SCBW     TBBW
#> Bayless 2.114461 152.6501 1.605122 7.513086   0 658.808   0 1.313281 30.86557
#> 
#> , , 1250_1300
#> 
#>              CWW      CBW    LMGRW      LTB      MMS      PBW      RRW     SCBW
#> Bayless 1.397752 109.7148 3.990371 3.486914 1.896962 530.2219 37.17403 3.264849
#>             TBBW
#> Bayless 17.13443
#> 
#> , , 1300_1350
#> 
#>               CWW      CBW    LMGRW LTB      MMS      PBW     RRW    SCBW TBBW
#> Bayless 0.4877879 70.63505 5.404507   0 11.10304 415.9701 214.826 4.42187    0
#>