ehymet: Methodologies for Functional Data Based on the Epigraph and Hypograph Indices (original) (raw)
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.
| Version: | 0.1.0 |
|---|---|
| Depends: | R (≥ 4.1) |
| Imports: | kernlab, stats, tf |
| Suggests: | ggplot2, knitr, MASS, rmarkdown, testthat (≥ 3.0.0), tidyr |
| Published: | 2024-06-14 |
| DOI: | 10.32614/CRAN.package.ehymet |
| Author: | Belen Pulido  [aut, cre], Jose Ignacio Diez [ctr] |
| Maintainer: | Belen Pulido |
| BugReports: | https://github.com/bpulidob/ehymet/issues |
| License: | MIT + file |
| URL: | https://github.com/bpulidob/ehymet,https://bpulidob.github.io/ehymet/ |
| NeedsCompilation: | no |
| Materials: | README NEWS |
| CRAN checks: | ehymet results |
Documentation:
Downloads:
Linking:
Please use the canonical formhttps://CRAN.R-project.org/package=ehymetto link to this page.