Publication

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

Wieringa, J. E., Gower, J. C., Dijksterhuis, G. B. & van Perlo-ten Kleij, F., 1-Oct-2009, In : Computational Statistics and Data Analysis. 53, 12, p. 4546-4554 9 p.

Research output: Contribution to journalArticleAcademicpeer-review

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. (c) 2009 Elsevier B.V. All rights reserved.

Original languageEnglish
Pages (from-to)4546-4554
Number of pages9
JournalComputational Statistics and Data Analysis
Volume53
Issue number12
Publication statusPublished - 1-Oct-2009

View graph of relations

ID: 1863605