A Critical Study of Usefulness of Selected Functional Classifiers in Economics

Daniel Kosiorowski; Dominik Mielczarek; Jerzy Piotr Rydlewski

doi:10.18778/0208-6018.347.05

Authors

Daniel Kosiorowski Cracow University of Economics, Department of Statistics https://orcid.org/0000-0002-3852-813X
Dominik Mielczarek AGH University of Science and Technology, Faculty of Applied Mathematics, Department of Mathematical Analysis, Computational Mathematics and Probability Methods https://orcid.org/0000-0002-5366-0550
Jerzy Piotr Rydlewski AGH University of Science and Technology, Faculty of Applied Mathematics, Department of Financial Mathematics https://orcid.org/0000-0002-2071-0646

DOI:

https://doi.org/10.18778/0208-6018.347.05

Keywords:

functional classifier, functional data analysis, robust methods, economic optimism barometer

Abstract

In this paper we conduct a critical analysis of the most popular functional classifiers. Moreover, we propose a new classifier for functional data. Some robustness properties of the functional classifiers are discussed as well. We can use an approach worked out in this paper to predict the expected state of the economy from aggregated Consumer Confidence Index (CCI, measuring consumers optimism) and Industrial Price Index (IPI, reflecting a degree of optimism in industry sector) exploiting not only scalar values of the indices but also the trajectories/shapes of functions describing the indices. Thus our considerations may be helpful in constructing a better economic barometer. As far as we know, this is the first comparison of functional classifiers with respect to a criterion of their usefulness in economic applications. The main result of the paper is a presentation of how a small fraction of outliers in a training sample, which are linearly independent from the training sample, consisting of almost linearly dependent functions, corrupt all analysed classifiers.

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