chemometrics (version 1.4.4)

pls2_nipals: 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)

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

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

Author

Peter Filzmoser <[e-mail]>

Details

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

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)