OutlierPCDist-class: Class "OutlierPCDist" - Outlier identification in high dimensions using using the PCDIST algorithm
Description
The function implements a simple, automatic outlier detection method suitable
for high dimensional data that treats each class independently and uses
a statistically principled threshold for outliers. The algorithm can
detect both mislabeled and abnormal samples without reference to other classes.
Arguments
Objects from the Class
Objects can be created by calls of the form new("OutlierPCDist", ...) but the
usual way of creating OutlierPCDist objects is a call to the function
OutlierPCDist() which serves as a constructor.
Slots
covobj:
A list containing intermediate results of the PCDIST algorithm for each class
k:
Number of selected PC
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
References
A.D. Shieh and Y.S. Hung (2009),
Detecting Outlier Samples in Microarray Data,
Statistical Applications in Genetics and Molecular Biology Vol. 8.
P. Filzmoser & V. Todorov (2012),
Robust tools for the imperfect world,
To appear.