pls2_nipals: PLS2 by NIPALS

In chemometrics: Multivariate Statistical Analysis in Chemometrics

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 <[e-mail]>

References

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

See Also

mvr, pls1_nipals

Examples

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

chemometrics documentation built on Aug. 25, 2023, 5:18 p.m.