biplot.princomp
Biplot for Principal Components
Produces a biplot (in the strict sense) from the output of
princomp
or prcomp
- Keywords
- multivariate, hplot
Usage
# S3 method for prcomp
biplot(x, choices = 1:2, scale = 1, pc.biplot = FALSE, …)# S3 method for princomp
biplot(x, choices = 1:2, scale = 1, pc.biplot = FALSE, …)
Arguments
- x
an object of class
"princomp"
.- choices
length 2 vector specifying the components to plot. Only the default is a biplot in the strict sense.
- scale
The variables are scaled by
lambda ^ scale
and the observations are scaled bylambda ^ (1-scale)
wherelambda
are the singular values as computed byprincomp
. Normally0 <= scale <= 1
, and a warning will be issued if the specifiedscale
is outside this range.- pc.biplot
If true, use what Gabriel (1971) refers to as a "principal component biplot", with
lambda = 1
and observations scaled up by sqrt(n) and variables scaled down by sqrt(n). Then inner products between variables approximate covariances and distances between observations approximate Mahalanobis distance.- …
optional arguments to be passed to
biplot.default
.
Details
This is a method for the generic function biplot
. There is
considerable confusion over the precise definitions: those of the
original paper, Gabriel (1971), are followed here. Gabriel and
Odoroff (1990) use the same definitions, but their plots actually
correspond to pc.biplot = TRUE
.
Side Effects
a plot is produced on the current graphics device.
References
Gabriel, K. R. (1971). The biplot graphical display of matrices with applications to principal component analysis. Biometrika, 58, 453--467. 10.2307/2334381.
Gabriel, K. R. and Odoroff, C. L. (1990). Biplots in biomedical research. Statistics in Medicine, 9, 469--485. 10.1002/sim.4780090502.
See Also
Examples
library(stats)
# NOT RUN {
require(graphics)
biplot(princomp(USArrests))
# }