ArchaeoPhases (version 1.1)

TempoPlot: Plot of the occurence of events

Description

A statistical graphic designed for the archaeological study of rhythms of the long term that embodies a theory of archaeological evidence for the occurrence of events.

Usage

TempoPlot(data, position, level = 0.95 , count = TRUE, Gauss = FALSE, 
title = "Tempo plot", x.label="Calendar Year", y.label="Cumulative events", 
line.types=c("solid", "12", "11", "28", "28"), plot.wi = 7, plot.ht = 7, 
base.font = 11, colors=TRUE, out.file=NULL)

Arguments

data

dataframe containing the output of the MCMC algorithm. The MCMC samples should be in calendar year (BC/AD).

position

numeric vector containing the position of the column corresponding to the MCMC chains of interest

level

probability corresponding to the level of confidence used for the credible interval

count

if TRUE the counting process is given as a number, otherwise it is a probability

Gauss

if TRUE, the Gaussian approximation of the CI is used

title

title of the graph

x.label

label of the x-axis

y.label

label of the y-axis

line.types

type of the lines drawn of the graph

plot.wi

width of the graph

plot.ht

height of the graph

base.font

font of the graph

colors

if TRUE, the graph is drawn with colors, otherwise it is drawn in black and white

out.file

the name of the graph + extension that will be saved if chosen. Null by default.

Value

It calculates the cumulative frequency of specified events by calculating how many events took place before each date in a specified range of dates. The result is given in calendar year (in format BC/AD).

Details

The tempo plot is one way to measure change over time: it estimates the cumulative occurrence of archaeological events in a Bayesian calibration. The tempo plot yields a graphic where the slope of the plot directly reflects the pace of change: a period of rapid change yields a steep slope and a period of slow change yields a gentle slope. When there is no change, the plot is horizontal. When change is instantaneous, the plot is vertical.

References

Dye, T.S. (2016) Long-term rhythms in the development of Hawaiian social stratification. Journal of Archaeological Science, 71, 1--9.

Examples

  data(Events); 
  TempoPlot(Events[1:1000,], c(2:5))
  TempoPlot(Events[1:1000,], c(2:5), count = TRUE)