biplot {stats} | R Documentation |
Plot a biplot on the current graphics device.
biplot(x, ...)
## Default S3 method:
biplot(x, y, var.axes = TRUE, col, cex = rep(par("cex"), 2),
xlabs = NULL, ylabs = NULL, expand = 1,
xlim = NULL, ylim = NULL, arrow.len = 0.1,
main = NULL, sub = NULL, xlab = NULL, ylab = NULL, ...)
x |
The |
y |
The second set of points (a two-column matrix), usually associated with variables. |
var.axes |
If |
col |
A vector of length 2 giving the colours for the first and
second set of points respectively (and the corresponding axes). If a
single colour is specified it will be used for both sets. If
missing the default colour is looked for in the
|
cex |
The character expansion factor used for labelling the points. The labels can be of different sizes for the two sets by supplying a vector of length two. |
xlabs |
A vector of character strings to label the first set of
points: the default is to use the row dimname of |
ylabs |
A vector of character strings to label the second set of
points: the default is to use the row dimname of |
expand |
An expansion factor to apply when plotting the second set of points relative to the first. This can be used to tweak the scaling of the two sets to a physically comparable scale. |
arrow.len |
The length of the arrow heads on the axes plotted in
|
xlim , ylim |
Limits for the x and y axes in the units of the first set of variables. |
main , sub , xlab , ylab , ... |
graphical parameters. |
A biplot is plot which aims to represent both the observations and
variables of a matrix of multivariate data on the same plot. There are
many variations on biplots (see the references) and perhaps the most
widely used one is implemented by biplot.princomp
.
The function biplot.default
merely provides the
underlying code to plot two sets of variables on the same figure.
Graphical parameters can also be given to biplot
: the size of
xlabs
and ylabs
is controlled by cex
.
a plot is produced on the current graphics device.
K. R. Gabriel (1971). The biplot graphical display of matrices with application to principal component analysis. Biometrika 58, 453–467.
J.C. Gower and D. J. Hand (1996). Biplots. Chapman & Hall.
biplot.princomp
, also for examples.