Wieringa, Jaap Dijksterhuis, Garmt Gower, John van Perlo, Frederieke
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.
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Volume (Year): 53 (2009) Issue (Month): 12 (October) Pages: 4546-4554 Download reference. The following formats are available: HTML
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