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ktaucenters  

Robust Clustering Procedures
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("ktaucenters", "1.0.0")



Attach the package and use:
library("ktaucenters")
Maintained by
Juan Domingo Gonzalez
[Scholar Profile | Author Map]
First Published: 2019-08-03
Latest Update: 2019-08-03
Description:
A clustering algorithm similar to K-Means is implemented, it has two main advantages, namely (a) The estimator is resistant to outliers, that means that results of estimator are still correct when there are atypical values in the sample and (b) The estimator is efficient, roughly speaking, if there are no outliers in the sample, results will be similar to those obtained by a classic algorithm (K-Means). Clustering procedure is carried out by minimizing the overall robust scale so-called tau scale. (see Gonzalez, Yohai and Zamar (2019) ).
How to cite:
Juan Domingo Gonzalez (2019). ktaucenters: Robust Clustering Procedures. R package version 1.0.0, https://cran.r-project.org/web/packages/ktaucenters. Accessed 14 May. 2025.
Previous versions and publish date:
0.1.0 (2019-08-03 10:20)
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Complete documentation for ktaucenters
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