Package: dcorVS 1.1
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:
dcorVS_1.1.tar.gz
dcorVS_1.1.tar.gz(r-4.5-noble)dcorVS_1.1.tar.gz(r-4.4-noble)
dcorVS_1.1.tgz(r-4.4-emscripten)dcorVS_1.1.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')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 15 days agofrom:ad3605c347. Checks:OK: 2. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Dec 10 2024 |
| R-4.5-linux | OK | Dec 10 2024 |
Exports:dcor.bsdcor.bsmmpcdcor.fbeddcor.mmpc
Dependencies:dcovRcppRcppArmadilloRcppGSLRcppParallelRcppZigguratRfast
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Variable Selection Algorithms Using the Distance Correlation. | dcorVS-package |
| Backward selection algorithms using the distance correlation | dcor.bs dcor.bsmmpc |
| MMPC and the FBED variable selection algorithms using the distance correlation | dcor.fbed dcor.mmpc |