Computes the aoristic sum.

```
aoristic(x, y, ...)
# S4 method for numeric,numeric
aoristic(
x,
y,
step = 1,
start = min(x, na.rm = TRUE),
stop = max(y, na.rm = TRUE),
weight = TRUE,
groups = NULL
)
# S4 method for list,missing
aoristic(
x,
step = 1,
start = min(x$from, na.rm = TRUE),
stop = max(x$to, na.rm = TRUE),
weight = FALSE,
groups = NULL
)
```

- x
A

`numeric`

vector. If`y`

is missing, must be a`list`

(or a`data.frame`

) with`numeric`

components (columns)`from`

and`to`

.- y
A

`numeric`

vector. If missing, an attempt is made to interpret`x`

in a suitable way.- ...
Currently not used.

- step
A length-one

`integer`

vector giving the step size, i.e. the width of each time step in the time series (in years CE; defaults to \(1\)).- start
A length-one

`numeric`

vector giving the beginning of the time window (in years CE).- stop
A length-one

`numeric`

vector giving the end of the time window (in years CE).- weight
A

`logical`

scalar: . Defaults to`FALSE`

(the aoristic sum is the number of elements within a time step).- groups
A

`factor`

vector in the sense that`as.factor(groups)`

defines the grouping. If`x`

is a`list`

(or a`data.frame`

),`groups`

can be a length-one vector giving the index of the grouping component (column) of`x`

.

An AoristicSum object.

Crema, E. R. (2012). Modelling Temporal Uncertainty in Archaeological
Analysis. *Journal of Archaeological Method and Theory*, 19(3): 440-61.
doi: 10.1007/s10816-011-9122-3
.

Johnson, I. (2004). Aoristic Analysis: Seeds of a New Approach to Mapping
Archaeological Distributions through Time. *In* Ausserer, K. F., Börner, W.,
Goriany, M. & Karlhuber-Vöckl, L. (ed.), *Enter the Past - The E-Way into
the Four Dimensions of Cultural Heritage*, Oxford: Archaeopress, p. 448-52.
BAR International Series 1227.
doi: 10.15496/publikation-2085

Ratcliffe, J. H. (2000). Aoristic Analysis: The Spatial Interpretation of
Unspecific Temporal Events. *International Journal of Geographical
Information Science*, 14(7): 669-79. doi: 10.1080/136588100424963
.

N. Frerebeau

```
## Aoristic Analysis
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)
)
## Keep only assemblages that have a sample size of at least 10
keep <- apply(X = zuni, MARGIN = 1, FUN = function(x) sum(x) >= 10)
## Calculate date ranges for each assemblage
span <- apply(
X = zuni[keep, ],
FUN = function(x, dates) {
z <- range(unlist(dates[x > 0]))
names(z) <- c("from", "to")
z
},
MARGIN = 1,
dates = dates
)
## Coerce to data.frame
span <- as.data.frame(t(span))
## Calculate aoristic sum (normal)
aorist_raw <- aoristic(span, step = 50, weight = FALSE)
plot(aorist_raw)
## Calculate aoristic sum (weights)
aorist_weigth <- aoristic(span, step = 50, weight = TRUE)
plot(aorist_weigth)
## Calculate aoristic sum (weights) by group
groups <- rep(c("A", "B", "C"), times = c(50, 90, 139))
aorist_groups <- aoristic(span, step = 50, weight = TRUE, groups = groups)
plot(aorist_groups)
## Rate of change
roc_weigth <- roc(aorist_weigth, n = 30)
plot(roc_weigth)
## Rate of change by group
roc_groups <- roc(aorist_groups, n = 30)
plot(roc_groups, facet = FALSE)
```