In this package, we provide functions to provide robust clustering in the case of Gaussian, Student and Laplace Mixture Models. Function RobVar computes robustly the covariance of a numerical data set which are realizations of Gaussian, Student or Laplace vectors. Function RobMM enables to provide a clustering of a numerical data set, RMMplot enables to produce graph for Robust Mixture Models, while Gen_MM enables to generate possibly contaminated mixture of Gaussian, Student and Laplace vectors.
tools:::Rd_package_author("RGMM")
Maintainer: tools:::Rd_package_maintainer("RGMM")
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
Vardi, Y. and Zhang, C.-H. (2000). The multivariate L1-median and associated data depth. Proc. Natl. Acad. Sci. USA, 97(4):1423-1426.