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.
tools:::Rd_package_author("Kmedians")
Maintainer: tools:::Rd_package_maintainer("Kmedians")
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.
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
Godichon-Baggioni, A. and Surendran, S. A penalized criterion for selecting the number of clusters for K-medians. arxiv.org/abs/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.