Activity Plot

Plots the first derivative of the tempo plot Bayesian estimate.

Usage

activity(object, ...)

# S4 method for EventsMCMC
activity(object, from = min(object), to = max(object), resolution = NULL)

# S4 method for CumulativeEvents
activity(object)

# S4 method for ActivityEvents
autoplot(object, ..., fill = "grey20")

# S4 method for ActivityEvents,missing
plot(x, fill = "grey20", ...)

# S4 method for ActivityEvents
multiplot(...)

Arguments

object: An EventsMCMC or a CumulativeEvents object.
...: Any ActivityEvents object.
from: A length-one numeric vector giving the earliest date to estimate for (in years).
to: A length-one numeric vector giving the latest date to estimate for (in years).
resolution: A length-one numeric vector specifying the temporal resolution (in years) at which densities are to be estimated. If NULL (the default), equally spaced points will be used (according to options("chronos.grid")).
fill: A character string specifying the colour to be used to fill the area under the curve.
x: An ActivityEvents object.

Value

activity() returns an ActivityEvents object.
autoplot() and multiplot return a ggplot object.
plot() is called it for its side-effects: it results in a graphic being displayed (invisibly returns x).

References

Dye, T. S. (2016). Long-term rhythms in the development of Hawaiian social stratification. Journal of Archaeological Science, 71: 1-9. doi:10.1016/j.jas.2016.05.006 .

Author

A. Philippe, M.-A. Vibet, T. S. Dye, N. Frerebeau

Examples

## Coerce to MCMC
eve <- as_events(events, calendar = "CE", iteration = 1)
eve <- eve[1:10000, ]

## Tempo plot
tmp <- tempo(eve)
plot(tmp, credible = TRUE, gauss = FALSE)

plot(tmp, credible = FALSE, gauss = TRUE)


## Activity plot
act <- activity(tmp)
plot(act)