Robust Clustering Procedures

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 than 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) ).


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install.packages("ktaucenters")

0.1.0 by Juan Domingo Gonzalez, 4 months ago


Browse source code at https://github.com/cran/ktaucenters


Authors: Juan Domingo Gonzalez [cre, aut] , Victor J. Yohai [aut] , Ruben H. Zamar [aut]


Documentation:   PDF Manual  


GPL (>= 2) license


Depends on MASS, methods, dplyr, dbscan, stats, GSE

Suggests jpeg, tclust, knitr


See at CRAN