screeplot {mva} | 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.

### See Also

`princomp`

.

### Examples

## The variances of the variables in the
## USArrests data vary by orders of magnitude, so scaling is appropriate
data(USArrests)
(pc.cr <- princomp(USArrests, cor = TRUE)) # inappropriate
screeplot(pc.cr)
data(Harman74.cor)
fit <- princomp(covmat=Harman74.cor)
screeplot(fit)
screeplot(fit, npcs=24, type="lines")