Comments on the NIPALS algorithm
作者:
Yoshikatsu Miyashita,
Toshiaki Itozawa,
Hiroyuki Katsumi,
Shin‐Ichi Sasaki,
期刊:
Journal of Chemometrics
(WILEY Available online 1990)
卷期:
Volume 4,
issue 1
页码: 97-100
ISSN:0886-9383
年代: 1990
DOI:10.1002/cem.1180040111
出版商: John Wiley&Sons, Ltd.
关键词: Matrix decomposition;NIPALS;Principal component;SIMCA;PLS
数据来源: WILEY
摘要:
AbstractThe Non‐linear Iterative Partial Least Squares (NIPALS) algorithm is used in principal component analysis to decompose a data matrix into score vectors and eigenvectors (loading vectors) plus a residual matrix. NIPALS starts with some guessed starting vector. The principal components obtained by NIPALS depends on the starting vector; the first principal component could not always be computed. Wold has suggested a starting vector for NIPALS, but we have found that even if this starting vector is used, the first principal component cannot be obtained in all cases. The reason why such a situation occurs is explained by the power method. A simple modification of the original NIPALS procedure to avoid getting smaller eigenvalues is presente
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