Package: ktaucenters 1.0.0

ktaucenters: 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 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>).

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

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NEWS

# Install 'ktaucenters' in R:
install.packages('ktaucenters', repos = c('https://jdgonzalezwork.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/jdgonzalezwork/ktaucenters/issues

Uses libs:
  • c++– GNU Standard C++ Library v3
Datasets:
  • mars_screw - Intensity and saturation values of a picture from mars.

On CRAN:

9 exports 1.10 score 45 dependencies 1 dependents 5 scripts 225 downloads

Last updated 8 months agofrom:e275af4830. Checks:OK: 9. Indexed: yes.

TargetResultDate
Doc / VignettesOKSep 17 2024
R-4.5-win-x86_64OKSep 17 2024
R-4.5-linux-x86_64OKSep 17 2024
R-4.4-win-x86_64OKSep 17 2024
R-4.4-mac-x86_64OKSep 17 2024
R-4.4-mac-aarch64OKSep 17 2024
R-4.3-win-x86_64OKSep 17 2024
R-4.3-mac-x86_64OKSep 17 2024
R-4.3-mac-aarch64OKSep 17 2024

Exports:derpsiOptimprovedktaucentersktaucentersktaucentersfastMscalenormal_consistency_constantspsiOptrhoOptrobinden

Dependencies:cellWiseclicolorspaceDEoptimRfansifarverggplot2gluegridExtraGSEgtableisobandlabelinglatticelifecyclemagrittrMASSMatrixmatrixStatsmgcvmunsellmvtnormnlmepcaPPpillarpkgconfigplyrR6RColorBrewerRcppRcppArmadilloreshape2rlangrobustbaserrcovscalesshapestringistringrsvdtibbleutf8vctrsviridisLitewithr