plotCorpusCa: Plotting 2D maps in correspondence analysis of corpus

Description

Graphical display of correspondence analysis of a corpus in two dimensions

Usage

plotCorpusCa(x, dim = c(1,2), map = "symmetric", what = c("all", "all"), 
             mass = c(FALSE, FALSE), contrib = c("none", "none"), 
             col = c("blue", "red"),
             col.text = c("black", "blue", "black", "red"),
             font = c(3, 4, 1, 2), pch = c(16, 1, 17, 24), 
             labels = c(2, 2), arrows = c(FALSE, FALSE),
             cex = 0.75,
             xlab = paste("Dimension", dim[1]),
             ylab = paste("Dimension", dim[2]), ...)

Arguments

Simple correspondence analysis object returned by runCorpusCa

dim

Numerical vector of length 2 indicating the dimensions to plot on horizontal and vertical axes respectively; default is first dimension horizontal and second dimension vertical.

map

Character string specifying the map type. Allowed options include "symmetric" (default) "rowprincipal" "colprincipal" "symbiplot" "rowgab" "colgab" "rowgreen" "colgr

what

Vector of two character strings specifying the contents of the plot. First entry sets the rows and the second entry the columns. Allowed values are "all" (all available points, default) "active" (only active points are displayed)

mass

Vector of two logicals specifying if the mass should be represented by the area of the point symbols (first entry for rows, second one for columns)

contrib

Vector of two character strings specifying if contributions (relative or absolute) should be represented by different colour intensities. Available options are "none" (contributions are not indicated in the plot). "absolute" (absolut

col

Vector of length 2 specifying the colours of row and column point symbols, by default blue for rows and red for columns. Colours can be entered in hexadecimal (e.g. "#FF0000"), rgb (e.g. rgb(1,0,0)) values or by R-name (e.g. "re

col.text

Vector of length 4 giving the color to be used for text of labels for row active and supplementary, column active and supplementary points. Colours can be entered in hexadecimal (e.g. "#FF0000"), rgb (e.g. rgb(1,0,0)) values or by R-

font

Vector of length 4 giving the font to be used for text labels for row active and supplementary, column active and supplementary points. See par for a list possible values.

pch

Vector of length 4 giving the type of points to be used for row active and supplementary, column active and supplementary points. See pchlist for a list of symbols.

labels

Vector of length two specifying if the plot should contain symbols only (0), labels only (1) or both symbols and labels (2). Setting labels to 2 results in the symbols being plotted at the coordinat

arrows

Vector of two logicals specifying if the plot should contain points (FALSE, default) or arrows (TRUE). First value sets the rows and the second value sets the columns.

cex

Numeric value indicating the size of the labels text.

xlab

Title for the x axis: see title.

ylab

Title for the y axis: see title.

...

Further arguments passed to plot, to points and to text.

itemize

kbd

"symbiplot"
"rowgab"
"colgab"
"rowgreen"
"colgreen"
"rowgab"
"colgab"
TRUE
"absolute"
"relative"

code

contrib

Details

The function plotCorpusCa makes a two-dimensional map of the object created by runCorpusCa with respect to two selected dimensions. By default the scaling option of the map is "symmetric", that is the so-called symmetric map. In this map both the row and column points are scaled to have inertias (weighted variances) equal to the principal inertia (eigenvalue or squared singular value) along the principal axes, that is both rows and columns are in pricipal coordinates. Other options are as follows:

{"rowprincipal" or "colprincipal" - these are the so-called asymmetric maps, with either rows in principal coordinates and columns in standard coordinates, or vice versa (also known as row-metric-preserving or column-metric-preserving respectively). These maps are biplots;}

References

Gabriel, K.R. and Odoroff, C. (1990). Biplots in biomedical research. Statistics in Medicine, 9, pp. 469-485. Greenacre, M.J. (1993) Correspondence Analysis in Practice. Academic Press, London. Greenacre, M.J. (1993) Biplots in correspondence Analysis, Journal of Applied Statistics, 20, pp. 251 - 269.