Graphical display of correspondence analysis results in two dimensions
# S3 method for ca
plot(x, dim = c(1,2), map = "symmetric", what = c("all", "all"),
mass = c(FALSE, FALSE), contrib = c("none", "none"),
col = c("blue", "red"),
pch = c(16, 21, 17, 24),
labels = c(2, 2),
arrows = c(FALSE, FALSE),
lines = c(FALSE, FALSE),
lwd=1,
xlab = "_auto_", ylab = "_auto_",
col.lab = c("blue", "red"), ...)Simple correspondence analysis object returned by ca
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.
Character string specifying the map type. Allowed options include "symmetric" (default) "rowprincipal" "colprincipal" "symbiplot" "rowgab" "colgab" "rowgreen" "colgreen"
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 ca using the options suprow and supcol.
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)
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.
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").
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.
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.
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.
Vector of two logicals specifying if the plot should join the points with lines (FALSE, default) or arrows (TRUE). First value sets the rows and the second value sets the columns.
Line width for arrows and lines
Labels for horizontal and vertical axes. The default, "_auto_" means that the function auto-generates a label of the form Dimension X (xx.xx %
Vector of length 2 specifying the colours of row and column point labels
In addition to the side effect of producing the plot, the function invisibly returns the coordinates
of the plotted points, a list of two components, with names rows and cols.
These can be used to further annotate the plot using base R plotting functions.
The function plot.ca makes a two-dimensional map of the object created by ca 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.
To globally resize all the points (and text labels), use par("cex"=) before the plot.
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. London: Academic Press. Greenacre, M.J. (1993) Biplots in correspondence Analysis, Journal of Applied Statistics, 20, pp. 251 - 269.
# NOT RUN {
data("smoke")
# A two-dimensional map with standard settings
plot(ca(smoke))
# Mass for rows and columns represented by the size of the point symbols
plot(ca(smoke), mass = c(TRUE, TRUE))
# Displaying the column profiles only with masses represented by size of point
# symbols and relative contributions by colour intensity.
# Since the arguments are recycled it is sufficient to give only one argument
# for mass and contrib.
data("author")
plot(ca(author), what = c("none", "all"), mass = TRUE, contrib = "relative")
# }
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