The Open UniversitySkip to content
 

Generalised procrustes analysis with optimal scaling: exploring data from a power supplier

Wieringa, Jaap; Dijksterhuis, Garmt; Gower, John and van Perlo, Frederieke (2009). Generalised procrustes analysis with optimal scaling: exploring data from a power supplier. Computational Statistics and Data Analysis, 53(12) pp. 4546–4554.

Full text available as:
[img]
Preview
PDF (Accepted Manuscript) - Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader
Download (690Kb)
DOI (Digital Object Identifier) Link: https://doi.org/10.1016/j.csda.2009.03.017
Google Scholar: Look up in Google Scholar

Abstract

Generalised Procrustes Analysis (GPA) is a method for matching several, possibly large, data sets by fitting them to each other using transformations, typically rotations. The linear version of GPA has been applied in a wide range of contexts. A non-linear extension of GPA is developed which uses Optimal Scaling (OS). The approach is suited to match data sets that contain nominal variables. A database of a Dutch power supplier that contains many categorical variables unfit for the usual linear GPA methodology is used to illustrate the approach.

Item Type: Journal Article
Copyright Holders: 2009 Elsevier
ISSN: 0167-9473
Academic Unit/Department: Faculty of Science, Technology, Engineering and Mathematics (STEM) > Mathematics and Statistics
Faculty of Science, Technology, Engineering and Mathematics (STEM)
Item ID: 17517
Depositing User: Colin Smith
Date Deposited: 02 Jul 2009 15:08
Last Modified: 06 Oct 2016 18:26
URI: http://oro.open.ac.uk/id/eprint/17517
Share this page:

Altmetrics

Scopus Citations

Download history for this item

These details should be considered as only a guide to the number of downloads performed manually. Algorithmic methods have been applied in an attempt to remove automated downloads from the displayed statistics but no guarantee can be made as to the accuracy of the figures.

▼ Automated document suggestions from open access sources

Actions (login may be required)

Policies | Disclaimer

© The Open University   + 44 (0)870 333 4340   general-enquiries@open.ac.uk