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.
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