OutlierSign2-class: Class '"OutlierSign2"' - Outlier identification in high...

In rrcovHD: Robust Multivariate Methods for High Dimensional Data

Description

Fast algorithm for identifying multivariate outliers in high-dimensional and/or large datasets, using spatial signs, see Filzmoser, Maronna, and Werner (CSDA, 2007). The computation of the distances is based on principal components.

Objects from the Class

Objects can be created by calls of the form new("OutlierSign2", ...) but the usual way of creating OutlierSign2 objects is a call to the function OutlierSign2() which serves as a constructor.

Slots

covobj:

A list containing intermediate results of the SIGN2 algorithm for each class

call, counts, grp, wt, flag, method, singularity:

from the "Outlier" class.

Extends

Class "Outlier", directly.

Methods

getCutoff

Return the cutoff value used to identify outliers

getDistance

Return a vector containing the computed distances

Author(s)

Valentin Todorov [e-mail]

References

P. Filzmoser, R. Maronna and M. Werner (2008). Outlier identification in high dimensions, Computational Statistics & Data Analysis, Vol. 52 1694–1711.

Filzmoser P & Todorov V (2013). Robust tools for the imperfect world, Information Sciences 245, 4–20. doi: 10.1016/j.ins.2012.10.017.

See Also

OutlierSign2, OutlierSign1, Outlier

Examples

showClass("OutlierSign2")

rrcovHD documentation built on April 23, 2021, 9:08 a.m.