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dcorVS  

Variable Selection Algorithms Using the Distance Correlation
View on CRAN: Click here


Download and install dcorVS package within the R console
Install from CRAN:
install.packages("dcorVS")

Install from Github:
library("remotes")
install_github("cran/dcorVS")

Install by package version:
library("remotes")
install_version("dcorVS", "1.1")



Attach the package and use:
library("dcorVS")
Maintained by
Michail Tsagris
[Scholar Profile | Author Map]
First Published: 2023-10-18
Latest Update: 2023-10-18
Description:
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. . Borboudakis G. and Tsamardinos I. (2019). "Forward-backward selection with early dropping". Journal of Machine Learning Research, 20(8): 1--39. . Huo X. and Szekely G.J. (2016). "Fast computing for distance covariance". Technometrics, 58(4): 435--447. .
How to cite:
Michail Tsagris (2023). dcorVS: Variable Selection Algorithms Using the Distance Correlation. R package version 1.1, https://cran.r-project.org/web/packages/dcorVS. Accessed 29 Mar. 2025.
Previous versions and publish date:
1.0 (2023-10-18 16:10)
Other packages that cited dcorVS R package
View dcorVS citation profile
Other R packages that dcorVS depends, imports, suggests or enhances
Complete documentation for dcorVS
Functions, R codes and Examples using the dcorVS R package
Some associated functions: dcor.bsmmpc . dcor.mmpc . dcorVS-package . 
Some associated R codes: dcor.bs.R . dcor.bsmmpc.R . dcor.fbed.R . dcor.mmpc.R .  Full dcorVS package functions and examples
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