chemometrics: pcaVarexpl – R documentation

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pcaVarexpl

PCA diagnostics for variables

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

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

`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`

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

ExplVar

explained variance for each variable

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

K. Varmuza and P. Filzmoser: Introduction to Multivariate Statistical Analysis in Chemometrics. CRC Press, Boca Raton, FL, 2009.

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

Multivariate Statistical Analysis in Chemometrics

v1.4.2

GPL (>= 3)

Authors

Peter Filzmoser and Kurt Varmuza

Initial release

2017-03-17