Variable Selection Algorithms Using the Distance Correlation R package dcorVS version 1.1 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>. Software Depends: R (>= 4.0) Imports: dcov, Rfast, stats Suggests: Rfast2 Michail Tsagris <mtsagris@uoc.gr> Comprehensive R Archive Network (CRAN) Michail Tsagris [aut, cre] GPL (>= 2) 2024-12-10 application/tgz https://CRAN.R-project.org/package=dcorVS doi:10.32614/CRAN.package.dcorVS