Generalised procrustes analysis with optimal scaling: Exploring data from a power supplierWieringa, 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 journal › Article › Academic › peer-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.
|Number of pages||9|
|Journal||Computational Statistics and Data Analysis|
|Publication status||Published - 1-Oct-2009|