MatrixCorrelation (version 0.10.1)

PCAcv: Principal Component Analysis cross-validation error

Description

PRESS values for PCA as implemented by Eigenvector and described by Bro et al. (2008).

Usage

PCAcv(X, ncomp)

Value

A vector of PRESS-values.

Arguments

X

matrix object to perform PCA on.

ncomp

integer number of components.

Author

Kristian Hovde Liland

Details

For each number of components predicted residual sum of squares are calculated based on leave-one-out cross-validation. The implementation ensures no over-fitting or information bleeding.

References

R. Bro, K. Kjeldahl, A.K. Smilde, H.A.L. Kiers, Cross-validation of component models: A critical look at current methods. Anal Bioanal Chem (2008) 390: 1241-1251.

See Also

plot.SMI (print.SMI/summary.SMI), RV (RV2/RVadj), r1 (r2/r3/r4/GCD), allCorrelations (matrix correlation comparison).

Examples

X1  <- scale( matrix( rnorm(100*300), 100,300), scale = FALSE)
PCAcv(X1,10)