Application of Interactive Regularized Discriminant Analysis to Wine Data

• Main Authors: Ute Römisch, Dimitar Vandev, Katrin Zur
• Format: Article
• Language: English
• Published: Austrian Statistical Society 2016-04-01
• Series: Austrian Journal of Statistics
• Online Access: http://www.ajs.or.at/index.php/ajs/article/view/347

Testing the possibility of determining the geographical origin (country) of wines on the base of chemico-analytical parameters was the aim of the European project ”Establishing of a wine data bank for analytical parameters for wines from Third countries (G6RD-CT-2001-00646-WINE DB)” supported by the European Commission. Therefore a data base containing 400 samples of commercial and authentic wines from Hungary, Czech Republic, Romania and South Africa was created. For each of those samples around 100 analytical parameters, among them rare earth elements and isotopic ratios were measured. Besides other multivariate statistical methods of discrimination and classification the method of regularized discriminant analysis (RDA) was used to distinguish the wines of the different countries on the base of a minimal number of the most important parameters. A MATLAB-program, developed by Vandev (2004) which allows an interactive stepwise discriminant model building on the base of an optimal choice of the “nonlinearity” parameter alpha was used. This program will be described shortly and models for commercial wines with corresponding classification and prediction error rates will be given. As a result of using RDA it was possible to reduce the number of analytical parameters to the eight to infer the geographical origin of these commercial wines.