Skip to contents

ehymet: Epigraph-Hypograph based methodologies for functional data

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.

  • 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 (2025). “Clustering multivariate functional data using the epigraph and hypograph indices: a case study on Madrid air quality.” Stochastic Environmental Research and Risk Assesment, 1-25. doi: 10.1007/s00477-025-02986-2

Installation

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

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

Funding

This package is part of the project/grant PDC2022-133359-I00 funded by MCIN/AEI/10.13039/501100011033 and by the European Union “NextGenerationEU/PRTR”.