Package: Dcurvature 0.0.4

Dcurvature: Discrete Curvature with 'shiny' Explorer

Implements discrete curvature estimation for ordered planar point sequences using circumcenter geometry on consecutive triplets, exposed through compiled C plus plus (C++) code via 'Rcpp' for speed and numerical robustness. The package is useful for objective elbow detection in multivariate workflows, especially principal component analysis (PCA), where selecting the number of retained components can be subjective. It provides a 'shiny' interface that supports upload of raw datasets or explained-variance tables, computes Kaiser-Meyer-Olkin (KMO) sampling-adequacy diagnostics, evaluates individual and cumulative variance curves, and reports curvature- based decision rules (m* and m**) with visual summaries for reproducible component-selection decisions. References: Arney et al. (2001); Axler (2024) <doi:10.1007/978-3-031-41026-0>; Bjorklund (2019) <doi:10.1111/evo.13835>; Burden and Faires (2015); Chang et al. (2023) <https://CRAN.R-project.org/package=shiny>; Christensen (2019); Cui (2020) <doi:10.18637/jss.v040.i08>; Eddelbuettel and Sanderson (2014) <doi:10.1016/j.csda.2013.02.005>; Engelke et al. (2023) <doi:10.1016/j.jseint.2023.04.010>; Gniazdowski (2021) <doi:10.26348/znwwsi.24.35>; Haynes et al. (2017); Jameel and Al-Salami (2023) <doi:10.24086/cuejhss.v7n1y2023.pp121-125>; Jolliffe (2002); Jolliffe and Cadima (2016) <doi:10.1098/rsta.2015.0202>; Kaiser (1974); Lehnert et al. (2019) <doi:10.18637/jss.v089.i12>; Ma and Dai (2011) <doi:10.1093/bib/bbq090>; Milligan (1995); Onumanyi et al. (2022) <doi:10.3390/app12157515>; Park (2010); Revelle (2024) <https://CRAN.R-project.org/package=psych>; Rodionova et al. (2021) <doi:10.1016/j.chemolab.2021.104304>; Sen and Cohen (2025) <doi:10.1177/01466216251344288>; Serneels and Verdonck (2008) <doi:10.1016/j.csda.2007.05.024>; Shi et al. (2021) <doi:10.1186/s13638-021-01910-w>; Shaukat et al. (2016) <doi:10.1515/eko-2016-0014>; Syakur et al. (2018) <doi:10.1088/1757-899X/336/1/012017>; Wickham and Bryan (2023) <https://CRAN.R-project.org/package=readxl>; Wu et al. (2017) <doi:10.1088/1755-1315/61/1/012054>; Youssef et al. (2023) <doi:10.21303/2461-4262.2023.002582>.

Authors:Aquiles Darghan [aut], Jorge Jola [aut, cre]

Dcurvature_0.0.4.tar.gz
Dcurvature_0.0.4.zip(r-4.7-x86_64)Dcurvature_0.0.4.zip(r-4.6-x86_64)Dcurvature_0.0.4.zip(r-4.5-x86_64)
Dcurvature_0.0.4.tgz(r-4.6-x86_64)Dcurvature_0.0.4.tgz(r-4.6-arm64)Dcurvature_0.0.4.tgz(r-4.5-x86_64)Dcurvature_0.0.4.tgz(r-4.5-arm64)
Dcurvature_0.0.4.tar.gz(r-4.7-arm64)Dcurvature_0.0.4.tar.gz(r-4.7-x86_64)Dcurvature_0.0.4.tar.gz(r-4.6-arm64)Dcurvature_0.0.4.tar.gz(r-4.6-x86_64)
Dcurvature_0.0.4.tgz(r-4.6-emscripten)
manual.pdf |manual.html
DESCRIPTION |NEWS
card.svg |card.png
Dcurvature/json (API)

# Install 'Dcurvature' in R:
install.packages('Dcurvature', repos = c('https://jorgejola-code.r-universe.dev', 'https://cloud.r-project.org'))
Uses libs:
  • c++– GNU Standard C++ Library v3

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

cpp

2.00 score 293 downloads 4 exports 43 dependencies

Last updated from:6c6a62e25a. Checks:13 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK157
linux-devel-x86_64OK167
source / vignettesOK254
linux-release-arm64OK159
linux-release-x86_64OK190
macos-release-arm64OK123
macos-release-x86_64OK272
macos-oldrel-arm64OK88
macos-oldrel-x86_64OK145
windows-develOK100
windows-releaseOK98
windows-oldrelOK83
wasm-releaseOK117

Exports:curvatureload_example_datarun_curvature_appselect_components

Dependencies:base64encbslibcachemcellrangerclicommonmarkcpp11crayondigestfastmapfontawesomefsgluehmshtmltoolshttpuvjquerylibjsonlitelaterlifecyclemagrittrmemoisemimeotelpillarpkgconfigprettyunitsprogresspromisesR6rappdirsRcppreadxlrematchrlangsassshinysourcetoolstibbleutf8vctrswithrxtable