OutlierPCDist-class | R Documentation |
"OutlierPCDist"
- Outlier identification in high dimensions using using the PCDIST algorithmThe 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.
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.
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.
Class "Outlier"
, directly.
Return the cutoff value used to identify outliers
Valentin Todorov valentin.todorov@chello.at
A.D. Shieh and Y.S. Hung (2009). Detecting Outlier Samples in Microarray Data, Statistical Applications in Genetics and Molecular Biology Vol. 8.
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")}.
OutlierPCDist
, Outlier
showClass("OutlierPCDist")
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