pca.nipals {mdatools}

NIPALS based PCA algorithm

Description

Calculates principal component space using non-linear iterative partial least squares algorithm (NIPALS)

Usage

pca.nipals(x, ncomp = min(ncol(x), nrow(x) - 1), tol = 10^-10)

Arguments

x

a matrix with data values (preprocessed)

ncomp

number of components to calculate

tol

tolerance (if difference in eigenvalues is smaller - convergence achieved)

Value

a list with scores, loadings and eigenvalues for the components

References

Geladi, Paul; Kowalski, Bruce (1986), "Partial Least Squares Regression:A Tutorial", Analytica Chimica Acta 185: 1-17