Package: Kmedians
Type: Package
Title: K-Medians
Version: 2.2.0
Authors@R: c(person("Antoine","Godichon-Baggioni", role = c("aut", "cre","cph"),
                      email = "antoine.godichon_baggioni@upmc.fr"),
               person("Sobihan","Surendran", role = "aut") )
Description: Online, Semi-online, and Offline K-medians algorithms are
    given. For both methods, the algorithms can be initialized
    randomly or with the help of a robust hierarchical
    clustering. The number of clusters can be selected with the
    help of a penalized criterion. We provide functions to provide
    robust clustering. Function gen_K() enables to generate a sample
    of data following a contaminated Gaussian mixture.
    Functions Kmedians() and Kmeans() consists in a K-median and a
    K-means algorithms while Kplot() enables to produce graph for both
    methods. 
    Cardot, H., Cenac, P. and Zitt, P-A. (2013). "Efficient and fast estimation of the geometric median in Hilbert spaces with an averaged stochastic gradient algorithm". Bernoulli, 19, 18-43. <doi:10.3150/11-BEJ390>.
    Cardot, H. and Godichon-Baggioni, A. (2017). "Fast Estimation of the Median Covariation Matrix with Application to Online Robust Principal Components Analysis". Test, 26(3), 461-480 <doi:10.1007/s11749-016-0519-x>.
    Godichon-Baggioni, A. and Surendran, S. "A penalized criterion for selecting the number of clusters for K-medians"     <arXiv:2209.03597> 
    Vardi, Y. and Zhang, C.-H. (2000). "The multivariate L1-median and associated data depth". Proc. Natl. Acad. Sci. USA, 97(4):1423-1426. <doi:10.1073/pnas.97.4.1423>.
License: GPL (>= 2)
Encoding: UTF-8
Imports: foreach, doParallel,parallel, genieclust, Gmedian,mvtnorm,
        capushe, ggplot2, reshape2
RoxygenNote: 7.1.2
NeedsCompilation: no
Packaged: 2023-12-18 13:26:49 UTC; Godichon-Baggioni
Author: Antoine Godichon-Baggioni [aut, cre, cph],
  Sobihan Surendran [aut]
Maintainer: Antoine Godichon-Baggioni <antoine.godichon_baggioni@upmc.fr>
Repository: CRAN
Date/Publication: 2023-12-18 13:40:05 UTC
Built: R 4.5.0; ; 2025-04-02 04:38:34 UTC; unix
