Biplot for Principal Components
## S3 method for class 'prcomp': biplot(x, choices = 1:2, scale = 1, pc.biplot = FALSE, \dots)
## S3 method for class 'princomp': biplot(x, choices = 1:2, scale = 1, pc.biplot = FALSE, \dots)
- an object of class
- length 2 vector specifying the components to plot. Only the default is a biplot in the strict sense.
- The variables are scaled by
lambda ^ scaleand the observations are scaled by
lambda ^ (1-scale)where
lambdaare the singular values as computed by
0 <= scale="" <="1, and a warning will be issued if the specified
scaleis outside this range.=>
- If true, use what Gabriel (1971) refers to as a "principal component
lambda = 1and 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
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
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.