Package: tclust 2.0-4

tclust: Robust Trimmed Clustering

Provides functions for robust trimmed clustering. The methods are described in Garcia-Escudero (2008) <doi:10.1214/07-AOS515>, Fritz et al. (2012) <doi:10.18637/jss.v047.i12>, Garcia-Escudero et al. (2011) <doi:10.1007/s11222-010-9194-z> and others.

Authors:Valentin Todorov [aut, cre], Luis Angel García Escudero [aut], Agustín Mayo Iscar [aut], Javier Crespo Guerrero [aut], Heinrich Fritz [aut]

tclust_2.0-4.tar.gz
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tclust_2.0-4.tgz(r-4.4-x86_64)tclust_2.0-4.tgz(r-4.4-arm64)tclust_2.0-4.tgz(r-4.3-x86_64)tclust_2.0-4.tgz(r-4.3-arm64)
tclust_2.0-4.tar.gz(r-4.5-noble)tclust_2.0-4.tar.gz(r-4.4-noble)
tclust_2.0-4.tgz(r-4.4-emscripten)tclust_2.0-4.tgz(r-4.3-emscripten)
tclust.pdf |tclust.html
tclust/json (API)

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

Peer review:

Bug tracker:https://github.com/valentint/tclust/issues

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
  • openmp– GCC OpenMP (GOMP) support library
Datasets:

On CRAN:

17 exports 3 stars 3.03 score 7 dependencies 3 dependents 10 mentions 61 scripts 2.1k downloads

Last updated 4 months agofrom:6d0eb288cb. Checks:OK: 9. Indexed: yes.

TargetResultDate
Doc / VignettesOKSep 06 2024
R-4.5-win-x86_64OKSep 06 2024
R-4.5-linux-x86_64OKSep 06 2024
R-4.4-win-x86_64OKSep 06 2024
R-4.4-mac-x86_64OKSep 06 2024
R-4.4-mac-aarch64OKSep 06 2024
R-4.3-win-x86_64OKSep 06 2024
R-4.3-mac-x86_64OKSep 06 2024
R-4.3-mac-aarch64OKSep 06 2024

Exports:ctlcurvesDiscrFactplot.ctlcurvesplot.DiscrFactplot.rlgplot.tclustplot.tkmeansprint.ctlcurvesprint.DiscrFactprint.tclustprint.tkmeansrlgsimula.rlgsimula.tclustsummary.DiscrFacttclusttkmeans

Dependencies:codetoolsdoParallelforeachiteratorsMASSRcppRcppArmadillo

A Trimming Approach to Cluster Analysis

Rendered fromtclust.rnwusingutils::Sweaveon Sep 06 2024.

Last update: 2024-05-09
Started: 2023-03-23