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

plot_bertin(object, ...)

plot_ford(object, ...)

# S4 method for CountMatrix
plot_bertin(object, threshold = NULL, scale = NULL)

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

## Arguments

object An object to be plotted. Currently not used. 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. 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. A logical scalar: should the EPPM be drawn (see below)?

## Value

A ggplot object.

## Details

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

## 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).

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.

eppm

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

N. Frerebeau

## Examples

# \donttest{
## Abundance data
## Coerce dataset to a count matrix
mississippi_count <- as_count(mississippi)

## Plot a Bertin diagram...
## ...without threshold
plot_bertin(mississippi_count, threshold = NULL) ## ...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(mississippi_count, threshold = mean, scale = scale_01) ## Abundance data
## Coerce dataset to a count matrix (data from Desachy 2004)
compiegne_count <- as_count(compiegne)

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