Plot Aoristic Analysis

Plot Aoristic Analysis

Usage

# S4 method for AoristicSum
autoplot(object, ..., facet = TRUE)

# S4 method for AoristicSum,missing
plot(x, facet = TRUE, ...)

# S4 method for RateOfChange
autoplot(object, ..., level = 0.95, facet = TRUE)

# S4 method for RateOfChange,missing
plot(x, level = 0.95, facet = TRUE, ...)

Arguments

object, x

An AoristicSum object.

...

Currently not used.

facet

A logical scalar: should a matrix of panels defined by groups be drawn?

level

A length-one numeric vector giving the confidence level.

Value

• autoplot() returns a ggplot object.

• plot() is called it for its side-effects: it results in a graphic being displayed (invisibly returns x).

See also

aoristic(), roc()

Other plotting methods: plot_event, plot_fit, plot_mcd, plot_time()

Author

N. Frerebeau

Examples

## Data from Husi 2022
data("loire", package = "folio")

## Get time range
loire_range <- loire[, c("lower", "upper")]

## Calculate aoristic sum (normal)
aorist_raw <- aoristic(loire_range, step = 50, weight = FALSE)
plot(aorist_raw)


## Calculate aoristic sum (weights)
aorist_weighted <- aoristic(loire_range, step = 50, weight = TRUE)
plot(aorist_weighted)


## Calculate aoristic sum (weights) by group
aorist_groups <- aoristic(loire_range, step = 50, weight = TRUE,
                          groups = loire$area)
plot(aorist_groups)


## Rate of change
roc_weighted <- roc(aorist_weighted, n = 30)
plot(roc_weighted)


## Rate of change by group
roc_groups <- roc(aorist_groups, n = 30)
plot(roc_groups)