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Methodologies for functional data based on the epigraph and hypograph indexes

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bpulidob/ehymet

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ehymet: Epigraph-Hypograph based methodologies for functional data

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The ehymet package define the epigraph, the hypograph and their modified versions for functional datasets in one and multiple dimensions. These indices allow to transform a functional dataset into a multivariate one, where usual clustering techniques can be applied. This package implements EHyClus method for clustering functional data in one or multiple dimension.

Related Papers:

  • Belén Pulido, Alba M. Franco-Pereira, Rosa E. Lillo (2023). “A fast epigraph and hypograph-based approach for clustering functional data.” Statistics and Computing, 33, 36. doi: 10.1007/s11222-023-10213-7

  • Belén Pulido, Alba M. Franco-Pereira, Rosa E. Lillo (2023). “The epigraph and the hypograph indices as useful tools for clustering multivariate functional data.” doi: 10.48550/arXiv.2307.16720

Installation

You can install the development version of ehymet from github using the remotes package:

# install.packages("remotes")
remotes::install_github("bpulidob/ehymet")

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Methodologies for functional data based on the epigraph and hypograph indexes

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