Biplot for Principal Components

biplot.princomp {stats}

R Documentation

Biplot for Principal Components

Description

Produces a biplot (in the strict sense) from the output of princomp or prcomp

Usage

## 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, ...)

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 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`.

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. doi: 10.2307/2334381.

Gabriel, K. R. and Odoroff, C. L. (1990). Biplots in biomedical research. Statistics in Medicine, 9, 469–485. doi: 10.1002/sim.4780090502.

Examples

require(graphics)
biplot(princomp(USArrests))

[Package stats version 3.5.0 Index]