plotCorpusCa: Plotting 2D maps in correspondence analysis of corpus

In RcmdrPlugin.temis: Graphical Integrated Text Mining Solution

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

x	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" "colgreen"
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) "passive" (only supplementary points are displayed) "none" (no points are displayed) The status (active or supplementary) of rows and columns is set in runCorpusCa using the options suprow and supcol.
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" (absolute contributions are indicated by colour intensities). "relative" (relative contributions are indicated by colour intensities). If set to "absolute" or "relative", points with zero contribution are displayed in white. The higher the contribution of a point, the closer the corresponding colour to the one specified by the col option.
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. "red").
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-name (e.g. "red").
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 coordinates and the labels with an offset.
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.

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;

• -"symbiplot" - this scales both rows and columns to have variances equal to the singular values (square roots of eigenvalues), which gives a symmetric biplot but does not preserve row or column metrics;

• -"rowgab" or "colgab" - these are asymmetric maps (see above) with rows (respectively, columns) in principal coordinates and columns (respectively, rows) in standard coordinates multiplied by the mass of the corresponding point. These are also biplots and were proposed by Gabriel & Odoroff (1990);

• -"rowgreen" or "colgreen" - these are similar to "rowgab" and "colgab" except that the points in standard coordinates are multiplied by the square root of the corresponding masses, giving reconstructions of the standardized residuals.

This function has options for sizing and shading the points. If the option mass is TRUE for a set of points, the size of the point symbol is proportional to the relative frequency (mass) of each point. If the option contrib is "absolute" or "relative" for a set of points, the colour intensity of the point symbol is proportional to the absolute contribution of the points to the planar display or, respectively, the quality of representation of the points in the display.

Author(s)

Oleg Nenadic (adapted from link{plot.ca} by Milan Bouchet-Valat)

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.

See Also

runCorpusCa, corpusCaDlg, summary.ca, print.ca, plot3d.ca, pchlist

RcmdrPlugin.temis documentation built on May 2, 2019, 5:21 p.m.