| OutlierSign1-class {rrcovHD} | R Documentation |
Class "OutlierSign1" - Outlier identification in high dimensions using the SIGN1 algorithm
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 Mahalanobis distances.
Objects from the Class
Objects can be created by calls of the form new("OutlierSign1", ...) but the
usual way of creating OutlierSign1 objects is a call to the function
OutlierSign1() which serves as a constructor.
Slots
covobj:A list containing intermediate results of the SIGN1 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 valentin.todorov@chello.at
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
OutlierSign1, OutlierSign2, Outlier
Examples
showClass("OutlierSign1")