Package: ktaucenters
Type: Package
Title: Robust Clustering Procedures
Version: 1.0.0
Authors@R: c(
  person("Juan Domingo", "Gonzalez", email = "juanrst@hotmail.com", role = c("cre", "aut")),
  person("Victor J.", "Yohai", email = "victoryohai@gmail.com", role = "aut"),
  person("Ruben H.", "Zamar", email = "ruben@stat.ubc.ca", role = "aut"),
  person("Douglas Alberto", "Carmona Guanipa", email = "douglas.albertocg@gmail.com", role = "aut")
  )
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)
        <arxiv:1906.08198>).
License: GPL (>= 2)
Encoding: UTF-8
Depends: R (>= 2.10), MASS, stats, GSE
Language: en-US
LazyData: true
RoxygenNote: 7.2.3
Suggests: jpeg, tclust, knitr, rmarkdown, testthat (>= 3.1.0)
Imports: Rcpp (>= 1.0.9)
LinkingTo: Rcpp
Config/testthat/edition: 3
NeedsCompilation: yes
Config/pak/sysreqs: libicu-dev
Repository: https://jdgonzalezwork.r-universe.dev
Date/Publication: 2024-01-21 16:03:19 UTC
RemoteUrl: https://github.com/jdgonzalezwork/ktaucenters
RemoteRef: HEAD
RemoteSha: e275af4830cffbb9947dabf2d563a96627d329e6
Packaged: 2026-06-20 07:10:13 UTC; root
Author: Juan Domingo Gonzalez [cre, aut],
  Victor J. Yohai [aut],
  Ruben H. Zamar [aut],
  Douglas Alberto Carmona Guanipa [aut]
Maintainer: Juan Domingo Gonzalez <juanrst@hotmail.com>