OutlierMahdist-class: Class OutlierMahdist - Outlier identification using
robust (mahalanobis) distances based on robust multivariate
location and covariance matrix
Description
Holds the results of outlier identification using robust mahalanobis
distances computed by robust multivarite location and covarince matrix.
Objects from the Class
Objects can be created by calls of the form new("OutlierMahdist", ...) but the
usual way of creating OutlierMahdist objects is a call to the function
OutlierMahdist() which serves as a constructor.Slots
covobj:- A list containing the robust estimates
of multivariate location and covariance matrix for each class
call:- Object of class
"language" counts:- Number of observations in each class
grp:- Grouping variable
wt:- Weights
flag:- 0/1 flags identifying the outliers
method:- Method used to compute the robust estimates
of multivariate location and covariance matrix
singularity:- a list with singularity
information for the covariance matrix (or
NULL
of not singular)
Extends
Class "Outlier", directly.Methods
- getCutoff
- Return the cutoff value used to identify outliers
- getDistance
- Return a vector containing the computed distances
References
Todorov V & Filzmoser P (2009),
An Object Oriented Framework for Robust Multivariate Analysis.
Journal of Statistical Software, 32(3), 1--47.
URL http://www.jstatsoft.org/v32/i03/.