| biplot.princomp {stats} | R Documentation |
Produces a biplot (in the strict sense) from the output of
princomp or prcomp
## S3 method for class 'prcomp': biplot(x, choices = 1:2, scale = 1, pc.biplot = FALSE, ...) ## S3 method for class 'princomp': biplot(x, choices = 1:2, scale = 1, pc.biplot = FALSE, ...)
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 by lambda ^ (1-scale) where
lambda are the singular values as computed by
princomp. Normally 0 <= scale <= 1, and a warning
will be issued if the specified scale 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. |
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.
a plot is produced on the current graphics device.
Gabriel, K. R. (1971). The biplot graphical display of matrices with applications to principal component analysis. Biometrika, 58, 453–467.
Gabriel, K. R. and Odoroff, C. L. (1990). Biplots in biomedical research. Statistics in Medicine, 9, 469–485.
data(USArrests) biplot(princomp(USArrests))