pls1_nipals: PLS1 by NIPALS

In chemometrics: Multivariate Statistical Analysis in Chemometrics

PLS1 by NIPALS

Description

NIPALS algorithm for PLS1 regression (y is univariate)

Usage

pls1_nipals(X, y, a, it = 50, tol = 1e-08, scale = FALSE)

Arguments

X	original X data matrix
y	original y-data
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 are only allowed to be univariate. This simplifies the algorithm.

Value

P	matrix with loadings for X
T	matrix with scores for X
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, pls2_nipals

Examples

data(PAC)
res <- pls1_nipals(PAC$X,PAC$y,a=5)

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