Package: dcorVS 1.0

Michail Tsagris

dcorVS: Variable Selection Algorithms Using the Distance Correlation

The 'FBED' and 'mmpc' variable selection algorithms have been implemented using the distance correlation. The references include: Tsamardinos I., Aliferis C. F. and Statnikov A. (2003). "Time and sample efficient discovery of Markovblankets and direct causal relations". In Proceedings of the ninth ACM SIGKDD international Conference. <doi:10.1145/956750.956838>. Borboudakis G. and Tsamardinos I. (2019). "Forward-backward selection with early dropping". Journal of Machine Learning Research, 20(8): 1--39. <doi:10.48550/arXiv.1705.10770>. Huo X. and Szekely G.J. (2016). "Fast computing for distance covariance". Technometrics, 58(4): 435--447. <doi:10.1080/00401706.2015.1054435>.

Authors:Michail Tsagris [aut, cre]

dcorVS_1.0.tar.gz
dcorVS_1.0.tar.gz(r-4.5-noble)dcorVS_1.0.tar.gz(r-4.4-noble)
dcorVS_1.0.tgz(r-4.4-emscripten)dcorVS_1.0.tgz(r-4.3-emscripten)
dcorVS.pdf |dcorVS.html
dcorVS/json (API)

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

Peer review:

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

1.00 score 142 downloads 4 exports 7 dependencies

Last updated 1 years agofrom:2f74392879. Checks:OK: 2. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 03 2024
R-4.5-linuxOKNov 03 2024

Exports:dcor.bsdcor.bsmmpcdcor.fbeddcor.mmpc

Dependencies:dcovRcppRcppArmadilloRcppGSLRcppParallelRcppZigguratRfast