liu.seSearch for publications in DiVA
Change search
ReferencesLink to record
Permanent link

Direct link
Partial least-squares vs. Lanczos bidiagonalization—I: analysis of a projection method for multiple regression
Linköping University, Department of Mathematics, Scientific Computing. Linköping University, The Institute of Technology.ORCID iD: 0000-0003-2281-856X
2004 (English)In: Computational Statistics & Data Analysis, ISSN 0167-9473, Vol. 46, no 1, 11-31 p.Article in journal (Refereed) Published
Abstract [en]

Multiple linear regression is considered and the partial least-squares method (PLS) for computing a projection onto a lower-dimensional subspace is analyzed. The equivalence of PLS to Lanczos bidiagonalization is a basic part of the analysis. Singular value analysis, Krylov subspaces, and shrinkage factors are used to explain why, in many cases, PLS gives a faster reduction of the residual than standard principal components regression. It is also shown why in some cases the dimension of the subspace, given by PLS, is not as small as desired.

Place, publisher, year, edition, pages
Elsevier, 2004. Vol. 46, no 1, 11-31 p.
Keyword [en]
partial least-squares; Lanczos bidiagonalization; singular value decomposition; principal components regression; Krylov subspace; chemometrics; shrinkage factors
National Category
URN: urn:nbn:se:liu:diva-22836DOI: 10.1016/S0167-9473(03)00138-5ISI: 000220929400002Local ID: 2174OAI: diva2:243149
Available from: 2009-10-07 Created: 2009-10-07 Last updated: 2015-03-27Bibliographically approved

Open Access in DiVA

No full text

Other links

Publisher's full text

Search in DiVA

By author/editor
Eldén, Lars
By organisation
Scientific ComputingThe Institute of Technology
In the same journal
Computational Statistics & Data Analysis

Search outside of DiVA

GoogleGoogle Scholar
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

Altmetric score

Total: 355 hits
ReferencesLink to record
Permanent link

Direct link