princomp
or prcomp
# 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, …)
"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
.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
.biplot
,
princomp
.require(graphics)
biplot(princomp(USArrests))
Run the code above in your browser using DataLab