Description Usage Arguments Details Value Author(s) References See Also Examples
Fast algorithm for identifying multivariate outliers in highdimensional and/or large datasets, using spatial signs, see Filzmoser, Maronna, and Werner (CSDA, 2007). The computation of the distances is based on Mahalanobis distances.
1 2 3 4 5  OutlierSign1(x, ...)
## Default S3 method:
OutlierSign1(x, grouping, qcrit = 0.975, trace=FALSE, ...)
## S3 method for class 'formula'
OutlierSign1(formula, data, ..., subset, na.action)

formula 
a formula with no response variable, referring only to numeric variables. 
data 
an optional data frame (or similar: see

subset 
an optional vector used to select rows (observations) of the
data matrix 
na.action 
a function which indicates what should happen
when the data contain 
... 
arguments passed to or from other methods. 
x 
a matrix or data frame. 
grouping 
grouping variable: a factor specifying the class for each observation. 
qcrit 
a numeric value between 0 and 1 indicating the quantile to be used as critical value for outlier detection (default to 0.975). 
trace 
whether to print intermediate results. Default is 
Based on the robustly sphered and normed data, robust principal components are computed. These are used for computing the covariance matrix which is the basis for Mahalanobis distances. A critical value from the chisquare distribution is then used as outlier cutoff.
An S4 object of class OutlierSign1
which
is a subclass of the virtual class Outlier
.
Valentin Todorov [email protected]
P. Filzmoser, R. Maronna and M. Werner (2008), Outlier identification in high dimensions, Computational Statistics & Data Analysis, Vol. 52 1694–1711.
P. Filzmoser & V. Todorov (2012), Robust tools for the imperfect world, To appear.
OutlierSign1
, OutlierSign2
, Outlier
1 2 3 4 5 6 7 8 9  data(hemophilia)
obj < OutlierSign1(gr~.,data=hemophilia)
obj
getDistance(obj) # returns an array of distances
getClassLabels(obj, 1) # returns an array of indices for a given class
getCutoff(obj) # returns an array of cutoff values (for each class, usually equal)
getFlag(obj) # returns an 0/1 array of flags
plot(obj, class=2) # standard plot function

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