pls1_nipals {chemometrics}R Documentation

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 <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, pls2_nipals

Examples

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

[Package chemometrics version 0.4 Index]