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ehymet

Methodologies for Functional Data Based on the Epigraph and Hypograph Indices

v0.1.1 · Nov 26, 2024 · MIT + file LICENSE

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>.

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Check History

OK 14 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE Mar 10, 2026

Code

Structure

Lines of code

4,518

Files

56

Compiled share

0%

Has compiled src

No

Language breakdown

R 1,881 (41.6%)Tests 391 (8.7%)Docs 626 (13.9%)Vignettes 1,620 (35.9%)

API

Exported functions

13

Internal functions

30

Recent export changes

v0.1.0+13 EHyClus, EI, HI +10 more

Testing & CI

Has tests

Yes

Test-to-code ratio

0.21

testthat edition

3

CI present

No

CI type

[]

PR gated

No

Docs

Return-value doc rate

100%

\dontrun example ratio

0%

Roxygen coverage

100%

Has pkgdown

No

NEWS present

Yes

Health & Security signals

Informational signals; not verdicts.

on.exit coverage

100%

Unsafe pattern score

0

Dep constraint coverage

0%

Secret pattern count

0

Bundled 3rd-party code

2 items

Portability & License

Min R version

4.1

System requirements

C++ standard

License

MIT + file LICENSE

License flags

SPDX valid, OSI approved

History

Versions

2

First release

2024-06-14

Latest release

2024-11-26

Avg cadence

165 days

Cold removal rate

Dep drift

1

LOC over versions

v0.1.0: 4,093 LOCv0.1.1: 4,518 LOC

Per-file churn detail lives in the source pipeline: https://github.com/r-observatory/cran-code-metrics.

Dependency Network

Dependencies Reverse dependencies clusterCrit kernlab tf ehymet

Version History

3 tracked
new 0.1.1 Mar 10, 2026
updated 0.1.1 ← 0.1.0 diff Nov 26, 2024
new 0.1.0 Jun 13, 2024