pls2_nipals {chemometrics}R Documentation

PLS2 by NIPALS

Description

NIPALS algorithm for PLS2 regression (y is multivariate)

Usage

pls2_nipals(X, Y, a, it = 50, tol = 1e-08, scale = FALSE)

Arguments

X original X data matrix
Y original Y-data matrix
a number of PLS components
it number of iterations
tol tolerance for convergence
scale if TRUE the X and y data will be scaled in addition to centering, if FALSE only mean centering is performed

Details

The NIPALS algorithm is the originally proposed algorithm for PLS. Here, the Y-data matrix is multivariate.

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
D D-matrix within the algorithm
W weights for X
C weights for Y
B final regression coefficients

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, pls1_nipals

Examples

data(cereal)
res <- pls2_nipals(cereal$X,cereal$Y,a=5)

[Package chemometrics version 0.4 Index]