princomp
.
biplot.princomp(x, choices=1:2, scale=1, pc.biplot=F, ...)
"princomp"
.
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.
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.
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 = T
.
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.