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 aCumulativeEvents
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. IfNULL
(the default), equally spaced points will be used (according tooptions("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 anActivityEvents
object.autoplot()
andmultiplot
return aggplot
object.plot()
is called it for its side-effects: it results in a graphic being displayed (invisibly returnsx
).
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 .
See also
Other event tools:
occurrence()
,
rec
,
roc()
,
tempo()