pls_eigen {chemometrics}R Documentation

Eigenvector algorithm for PLS

Description

Computes the PLS solution by eigenvector decompositions.

Usage

pls_eigen(X, Y, a)

Arguments

X X input data, centered (and scaled)
Y Y input data, centered (and scaled)
a number of PLS components

Details

The X loadings (P) and scores (T) are found by the eigendecomposition of X'YY'X. The Y loadings (Q) and scores (U) come from the eigendecomposition of Y'XX'Y. The resulting P and Q are orthogonal. The first score vectors are the same as for standard PLS, subsequent score vectors different.

Value

P matrix with loadings for X
T matrix with scores for X
Q matrix with loadings for Y
U matrix with scores for Y

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

mvr

Examples

data(cereal)
res <- pls_eigen(cereal$X,cereal$Y,a=6)

[Package chemometrics version 0.4 Index]