RGMM-package: Robust Mixture Model
In RGMM: Robust Mixture Model

RGMM-package

R Documentation

Robust Mixture Model

Description

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.

Author(s)

Antoine Godichon-Baggioni [aut, cre, cph], Stéphane Robin [aut]

Maintainer: Antoine Godichon-Baggioni <antoine.godichon_baggioni@upmc.fr>

References

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.

RGMM documentation built on Nov. 24, 2023, 5:10 p.m.