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Statistical Papers

, Volume 60, Issue 3, pp 629–640 | Cite as

Classification rules based on distribution functions of functional depth

  • Olusola Samuel MakindeEmail author
Regular Article

Abstract

In ordering multivariate objects, the use of data depth provides a centre-outward ranking. The notion of data depth has been extended to functional data setting and applied in classifying functional data, for example maximal depth classification rules. In this paper, we explore notions of functional depth and propose a classification method based on distribution functions of data depth for functional data. The performance of this method is examined by using simulations and real data sets and the results are compared with the results from existing methods.

Keywords

Classification rules Distribution function Functional data Data depth Error rate 

Notes

Acknowledgements

We are thankful to two anonymous referees and Editor-in-Chief whose comments have substantially improved the contents of this paper.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2016

Authors and Affiliations

  1. 1.Department of StatisticsFederal University of TechnologyAkureNigeria

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