restlos (version 0.2-2)

restlos-package: Robust Estimation of Location and Scatter

Description

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.

Details

Package:

restlos

Type:

Package

Version:

0.2-2

Date:

2015-08-09

License:

GPL (>= 2)

LazyLoad:

yes

References

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.