Supervised classification for functional data: A weighted distance approach

Andrés M. Alonso, David Casado and Juan Romo

Computational Statistics & Data Analysis, 2012, vol. 56, issue 7, 2334-2346

Abstract: A natural methodology for discriminating functional data is based on the distances from the observation or its derivatives to group representative functions (usually the mean) or their derivatives. It is proposed to use a combination of these distances for supervised classification. Simulation studies show that this procedure performs very well, resulting in smaller testing classification errors. Applications to real data show that this technique behaves as well as–and in some cases better than–existing supervised classification methods for functions.

Keywords: Supervised classification; Discriminant analysis; Functional data; Weighted distances (search for similar items in EconPapers)
Date: 2012
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Citations: View citations in EconPapers (12)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:csdana:v:56:y:2012:i:7:p:2334-2346

DOI: 10.1016/j.csda.2012.01.013

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