Package: didec 1.1.0

didec: Directed Dependence Coefficient

Directed Dependence Coefficient (didec) is a measure of functional dependence. Multivariate Feature Ordering by Conditional Independence (MFOCI) is a variable selection algorithm based on didec. Hierarchical Variable Clustering (VarClustPartition) is a variable clustering method based on didec. For more information, see the paper by Ansari and Fuchs (2025, <doi:10.48550/arXiv.2212.01621>), and the paper by Fuchs and Wang (2024, <doi:10.1016/j.ijar.2024.109185>).

Authors:Yuping Wang [aut, cre], Sebastian Fuchs [aut], Jonathan Ansari [aut]

didec_1.1.0.tar.gz
didec_1.1.0.zip(r-4.7-any)didec_1.1.0.zip(r-4.6-any)didec_1.1.0.zip(r-4.5-any)
didec_1.1.0.tgz(r-4.6-any)didec_1.1.0.tgz(r-4.5-any)
didec_1.1.0.tar.gz(r-4.7-any)didec_1.1.0.tar.gz(r-4.6-any)
didec_1.1.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
didec/json (API)

# Install 'didec' in R:
install.packages('didec', repos = c('https://yupingwang7.r-universe.dev', 'https://cloud.r-project.org'))
Datasets:

On CRAN:

Conda:

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

1.00 score 1 stars 277 downloads 3 exports 44 dependencies

Last updated from:4690b941ff. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develOK121
source / vignettesOK200
linux-releaseOK149
macos-releaseOK191
macos-oldrelOK147
windows-develOK94
windows-releaseOK81
windows-oldrelOK86
wasm-releaseOK105

Exports:didecmfociVarClustPartition

Dependencies:apeclicopBasiccowplotcpp11data.tabledendextenddigestfarverFOCIggplot2gluegmpgoftestgridExtragtablegtoolsisobandlabelinglatticelifecyclelmomcoLmomentsmagrittrMASSmvtnormnlmepcaPPphylogramproxyR6randtoolboxRANNRColorBrewerRcppRcppArmadillorlangrngWELLS7scalesvctrsviridisviridisLitewithr