plot_bar: Bar Plot

Description Usage Arguments Details Value Bertin Matrix EPPM Author(s) References See Also Examples

Description

Plots a Bertin, Ford (battleship curve) or Dice-Leraas diagram.

Usage

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plot_bertin(object, ...)

plot_ford(object, ...)

## S4 method for signature 'matrix'
plot_bertin(object, threshold = NULL, scale = NULL)

## S4 method for signature 'matrix'
plot_ford(object)

## S4 method for signature 'CountMatrix'
plot_ford(object, EPPM = FALSE)

Arguments

object

An abundance matrix to be plotted.

...

Currently not used.

threshold

A function that takes a numeric vector as argument and returns a numeric threshold value (see below). If NULL (the default), no threshold is computed.

scale

A function used to scale each variable, that takes a numeric vector as argument and returns a numeric vector. If NULL (the default), no scaling is performed.

EPPM

A logical scalar: should the EPPM be drawn (see below)?

Details

If EPPM is TRUE and if a relative abundance is greater than the mean percentage of the type, the exceeding part is highlighted.

Value

A ggplot2::ggplot object.

Bertin Matrix

As de Falguerolles et al. (1997) points out: "In abstract terms, a Bertin matrix is a matrix of displays. ... To fix ideas, think of a data matrix, variable by case, with real valued variables. For each variable, draw a bar chart of variable value by case. High-light all bars representing a value above some sample threshold for that variable."

EPPM

This positive difference from the column mean percentage (in french "écart positif au pourcentage moyen", EPPM) represents a deviation from the situation of statistical independence. As independence can be interpreted as the absence of relationships between types and the chronological order of the assemblages, EPPM is a useful graphical tool to explore significance of relationship between rows and columns related to seriation (Desachy 2004).

Author(s)

N. Frerebeau

References

Bertin, J. (1977). La graphique et le traitement graphique de l'information. Paris: Flammarion. Nouvelle Bibliothèque Scientifique.

de Falguerolles, A., Friedrich, F. & Sawitzki, G. (1997). A Tribute to J. Bertin's Graphical Data Analysis. In W. Badilla & F. Faulbaum (eds.), SoftStat '97: Advances in Statistical Software 6. Stuttgart: Lucius & Lucius, p. 11-20.

Desachy, B. (2004). Le sériographe EPPM: un outil informatisé de sériation graphique pour tableaux de comptages. Revue archéologique de Picardie, 3(1), 39-56. doi: 10.3406/pica.2004.2396.

Ford, J. A. (1962). A quantitative method for deriving cultural chronology. Washington, DC: Pan American Union. Technical manual 1.

See Also

eppm()

Other plot: plot_diversity, plot_line, plot_matrix, plot_spot()

Examples

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## Abundance data
## Coerce dataset to a count matrix
data("mississippi", package = "folio")
counts1 <- as_count(mississippi)

## Plot a Bertin diagram...
## ...without threshold
plot_bertin(counts1)
## ...with variables scaled to 0-1 and the variable mean as threshold
scale_01 <- function(x) (x - min(x)) / (max(x) - min(x))
plot_bertin(counts1, threshold = mean, scale = scale_01)

## Abundance data
## Coerce dataset to a count matrix (data from Desachy 2004)
data("compiegne", package = "folio")
counts2 <- as_count(compiegne)

## Plot a Ford diagram...
## ...without threshold
plot_ford(counts2)
## ...with EPPM
plot_ford(counts2, EPPM = TRUE)

tabula documentation built on May 25, 2021, 5:11 p.m.