R: Screeplot of PCA Results

screeplot {stats}

R Documentation

Screeplot of PCA Results

Description

screeplot plots the variances against the number of the principal component. This is also the plot method for class "princomp".

Usage

screeplot(x, npcs = min(10, length(x$sdev)),
          type = c("barplot", "lines"),
          main = deparse(substitute(x)), ...)

Arguments

`x`	an object of class `"princomp"`, as from `princomp()`.
`npcs`	the number of principal components to be plotted.
`type`	the type of plot.
`main, ...`	graphics parameters.

References

Mardia, K. V., J. T. Kent and J. M. Bibby (1979). Multivariate Analysis, London: Academic Press.

Venables, W. N. and B. D. Ripley (2002). Modern Applied Statistics with S, Springer-Verlag.

Examples

## The variances of the variables in the
## USArrests data vary by orders of magnitude, so scaling is appropriate
(pc.cr <- princomp(USArrests, cor = TRUE))  # inappropriate
screeplot(pc.cr)

fit <- princomp(covmat=Harman74.cor)
screeplot(fit)
screeplot(fit, npcs=24, type="lines")