A statistical graphic designed for the archaeological study of when events of a specified kind occurred
OccurrencePlot(
data,
position,
plot.result = NULL,
level = 0.95,
intervals = "CI",
title = "Occurrence plot",
subtitle = NULL,
caption = "ArchaeoPhases",
labelXaxis = "Calendar year",
labelYaxis = NULL,
language = "English",
occurrence = "occurrence",
height = 7,
width = 7,
units = "in",
x.min = NULL,
x.max = NULL,
x.scale = "calendar",
elapsed.origin.position = NULL,
dumbbell.size = 1,
dot.guide = FALSE,
dot.guide.size = 0.25,
y.grid = FALSE,
file = NULL,
newWindow = TRUE,
print.data.result = FALSE
)
Data frame containing the output of the MCMC algorithm.
Numeric vector containing the position of the column corresponding to the MCMC chains of interest.
If TRUE
, then draw a plot on the display,
else suppress drawing.
Probability corresponding to the level of confidence.
One of "CI" for credible intervals or "HPD" for highest posterior density intervals.
Title of the plot.
Subtitle of the plot.
Caption of the plot.
Label of the x-axis.
Label of the y-axis.
String indicating a language recognized by the toOrdinal package.
String to append to each y-axis tic label.
Plot height in units
.
Plot width in units
.
String recognized by the ggsave()
function,
one of "in", "cm", "mm".
Minimum x-axis value.
Maximum x-axis value.
One of "calendar" for calendar years, "BP" for years before present, or "elapsed" for time elapsed from a specified origin.
Position of the column to use as the origin for elapsed time calculations.
Size of the plot symbol.
Switch for a horizontal guide from the y axis.
Size of the dot guide.
Switch for horizontal grid lines.
Name of the file that will be saved if specified.
If NULL
no plot will be saved.
Whether or not the plot is drawn within a new window.
If TRUE
, the list containing the data
to plot will be returned.
NULL
, called for its side effects. It may also return
a list containing the data to plot (if print.data.result = TRUE
).
If we have k events, then we can estimate the calendar date t corresponding to the
smallest date such that the number of events observed before t is equal to k.
The OccurrencePlot()
estimates these occurrences and gives the credible
interval or the highest posterior density (HPD) region with a desired level of confidence.
# NOT RUN {
data(Events);
OccurrencePlot(Events[1:1000, ], c(2:5), print.data.result = FALSE)
# }
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