pcaVarexpl {chemometrics}R Documentation

PCA diagnostics for variables

Description

Diagnostics of PCA to see the explained variance for each variable.

Usage

pcaVarexpl(X, a, center = TRUE, scale = TRUE, plot = TRUE, ...)

Arguments

X numeric data frame or matrix
a number of principal components
center centring of X (FALSE or TRUE)
scale scaling of X (FALSE or TRUE)
plot if TRUE make plot with explained variance
... additional graphics parameters, see par

Details

For a desired number of principal components the percentage of explained variance is computed for each variable and plotted.

Value

ExplVar explained variance for each variable

Author(s)

Peter Filzmoser <P.Filzmoser@tuwien.ac.at>

References

K. Varmuza and P. Filzmoser: Introduction to Multivariate Statistical Analysis in Chemometrics. CRC Press. To appear.

See Also

princomp

Examples

data(glass)
res <- pcaVarexpl(glass,a=2)

[Package chemometrics version 0.4 Index]