restlos-package: Robust Estimation of Location and Scatter

Description Details Author(s) References


The restlos package provides algorithms for robust estimation of location (mean and mode) and scatter based on minimum spanning trees (pMST), self-organizing maps (Flood Algorithm), Delaunay triangulations (RDELA), and nested minimum volume convex sets (MVCH). The functions are also suitable for outlier detection.


Package: restlos
Type: Package
Version: 0.2-2
Date: 2015-08-09
License: GPL (>= 2)
LazyLoad: yes


Steffen Liebscher and Thomas Kirschstein

Maintainer: Steffen Liebscher <>


Kirschstein, T., Liebscher, S., and Becker, C. (2013): Robust estimation of location and scatter by pruning the minimum spanning tree, Journal of Multivariate Analysis, 120, 173-184, DOI: 10.1016/j.jmva.2013.05.004.

Kirschstein, T., Liebscher, S., Porzio, G., Ragozini, G. (2015): Minimum volume peeling: a robust non-parametric estimator of the multivariate mode, Computational Statistics and Data Analysis, DOI: 10.1016/j.csda.2015.04.012.

Liebscher, S., Kirschstein, T. (2015): Efficiency of the pMST and RDELA Location and Scatter Estimators, AStA-Advances in Statistical Analysis, 99(1), 63-82, DOI: 10.1007/s10182-014-0231-7.

Liebscher, S., Kirschstein, T., and Becker, C. (2012): The Flood Algorithm - A Multivariate, Self-Organizing-Map-Based, Robust Location and Covariance Estimator, Statistics and Computing, 22(1), 325-336, DOI: 10.1007/s11222-011-9250-3.

Liebscher, S., Kirschstein, T., and Becker, C. (2013): RDELA - A Delaunay-Triangulation-based, Location and Covariance Estimator with High Breakdown Point, Statistics and Computing, DOI: 10.1007/s11222-012-9337-5.

restlos documentation built on May 2, 2019, 2:45 p.m.