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The ehymet (Methodologies for functional data based on the epigraph and hypograph indices) 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.
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
You can install the development version of ehymet from github using the remotes package:
# install.packages("remotes")
remotes::install_github("bpulidob/ehymet")These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.