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

In rrcovHD: Robust Multivariate Methods for High Dimensional Data

Class "OutlierPCOut" - Outlier identification in high dimensions using using the PCOUT algorithm

Description

Holds the results of outlier identification using the PCOUT algorithm.

Objects from the Class

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

Slots

covobj:

A list containing intermediate results of the PCOUT 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

plot

Plot the results of the outlier detection process

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. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1016/j.ins.2012.10.017")}.

See Also

OutlierPCOut, "Outlier"

Examples

showClass("OutlierMahdist")

rrcovHD documentation built on Sept. 12, 2024, 7:11 a.m.