Classification of functional data: a weighted distance approach
AbstractA popular approach for classifying functional data is based on the distances from the function or its derivatives to group representative (usually the mean) functions or their derivatives. In this paper, we propose using a combination of those distances. Simulation studies show that our procedure performs very well, resulting in smaller testing classication errors. Applications to real data show that our procedure performs as well as –and in some cases better than– other classication methods.
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Bibliographic InfoPaper provided by Universidad Carlos III, Departamento de Estadística y Econometría in its series Statistics and Econometrics Working Papers with number ws093915.
Date of creation: Jul 2009
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Discriminant analysis; Functional data; Weighted distances;
This paper has been announced in the following NEP Reports:
- NEP-ALL-2010-05-22 (All new papers)
- NEP-ECM-2010-05-22 (Econometrics)
- NEP-NEU-2010-05-22 (Neuroeconomics)
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