PCAcv {MatrixCorrelation} | R Documentation |
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)
Arguments
X |
|
ncomp |
|
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.
Value
A vector of PRESS-values.
Author(s)
Kristian Hovde Liland
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)
[Package MatrixCorrelation version 0.10.0 Index]