DESCRIPTION

Package: ehymet
Title: Methodologies for Functional Data Based on the Epigraph and Hypograph Indices
Version: 0.1.1
Authors@R: c(
    person(given = "Belen", family = "Pulido", role = c("aut", "cre"),
           email = "bpulidob4@gmail.com", 
           comment = c(ORCID = "0000-0003-2105-959X")),
    person(given = "Jose Ignacio", family = "Diez", role = c("ctr"))
  )
Description: Implements methods for functional data analysis based on the epigraph 
  and hypograph indices. These methods transform 
  functional datasets, whether in one or multiple dimensions, into multivariate 
  datasets. The transformation involves applying the epigraph, hypograph, and 
  their modified versions to both the original curves and their first and second 
  derivatives. The calculation of these indices is tailored to the dimensionality 
  of the functional dataset, with special considerations for dependencies between 
  dimensions in multidimensional cases. This approach extends traditional multivariate
  data analysis techniques to the functional data setting. A key application of 
  this package is the EHyClus method, which enhances clustering analysis for 
  functional data across one or multiple dimensions using the epigraph and 
  hypograph indices. See Pulido et al. (2023) <doi:10.1007/s11222-023-10213-7>
  and Pulido et al. (2024) <doi:10.48550/arXiv.2307.16720>.
License: MIT + file LICENSE
Encoding: UTF-8
URL: https://github.com/bpulidob/ehymet, https://bpulidob.github.io/ehymet/
BugReports: https://github.com/bpulidob/ehymet/issues
Depends:
  R (>= 4.1)
Imports: 
  clusterCrit,
  kernlab,
  stats,
  tf
Suggests: 
  ggplot2,
  knitr,
  MASS,
  parallel,
  rmarkdown,
  testthat (>= 3.0.0),
  tidyr
Roxygen: list(markdown = TRUE)
RoxygenNote: 7.3.2
Config/testthat/edition: 3
VignetteBuilder: knitr