Produces an abundance *vs* time diagram.

```
# S4 method for IncrementTest
autoplot(object, ..., level = 0.95, roll = FALSE, window = 3)
# S4 method for IncrementTest,missing
plot(x, level = 0.95, roll = FALSE, window = 3)
```

- object, x
An object to be plotted.

- ...
Currently not used.

- level
A length-one

`numeric`

vector giving the confidence level.- roll
A

`logical`

scalar: should each time series be subsetted to look for episodes of selection?- window
An odd

`integer`

giving the size of the rolling window. Only used if`roll`

is`TRUE`

.

Results of the frequency increment test can be displayed on an abundance
*vs* time diagram aid in the detection and quantification of selective
processes in the archaeological record. If `roll`

is `TRUE`

, each time
series is subsetted according to `window`

to see if episodes of selection
can be identified among decoration types that might not show overall
selection. If so, shading highlights the data points where
`fit()`

identifies selection.

Displaying FIT results on an abundance *vs* time diagram is adapted from Ben
Marwick's original idea.

Other plotting methods:
`plot_aoristic`

,
`plot_event`

,
`plot_mcd`

,
`plot_time()`

N. Frerebeau

```
data("merzbach", package = "folio")
## Coerce the merzbach dataset to a count matrix
## Keep only decoration types that have a maximum frequency of at least 50
keep <- apply(X = merzbach, MARGIN = 2, FUN = function(x) max(x) >= 50)
counts <- as_count(merzbach[, keep])
## Group by phase
## We use the row names as time coordinates (roman numerals)
dates <- as.numeric(utils::as.roman(rownames(counts)))
## Frequency Increment Test
freq <- fit(counts, dates)
## Plot time vs abundance and highlight selection
plot(freq)
plot(freq, roll = TRUE, window = 5)
```