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QuClu  

Quantile-Based Clustering Algorithms
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("QuClu", "1.0.1")



Attach the package and use:
library("QuClu")
Maintained by
Laura Anderlucci
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2018-07-30
Latest Update: 2022-05-26
Description:
Various quantile-based clustering algorithms: algorithm CU (Common theta and Unscaled variables), algorithm CS (Common theta and Scaled variables through lambda_j), algorithm VU (Variable-wise theta_j and Unscaled variables) and algorithm VW (Variable-wise theta_j and Scaled variables through lambda_j). Hennig, C., Viroli, C., Anderlucci, L. (2019) "Quantile-based clustering." Electronic Journal of Statistics. 13 (2) 4849 - 4883 .
How to cite:
Laura Anderlucci (2018). QuClu: Quantile-Based Clustering Algorithms. R package version 1.0.1, https://cran.r-project.org/web/packages/QuClu. Accessed 21 Dec. 2024.
Previous versions and publish date:
0.1.0 (2018-07-30 11:00)
Other packages that cited QuClu R package
View QuClu citation profile
Other R packages that QuClu depends, imports, suggests or enhances
Complete documentation for QuClu
Functions, R codes and Examples using the QuClu R package
Some associated functions: alg.CS . alg.CU . alg.VS . alg.VU . kquantiles . 
Some associated R codes: alg.CS.R . alg.CU.R . alg.VS.R . alg.VU.R . kquantiles.R .  Full QuClu package functions and examples
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