An S4 class to store the result of outlier detection.
samples
A character
vector to store the sample identifiers.
groups
A factor
vector to store the group names.
standard
A numeric
matrix giving the standard squared Mahalanobis
distances.
robust
A numeric
matrix giving the robust squared Mahalanobis
distances.
limit
A numeric
value giving the cut-off value used for outliers
detection (quantile of the Chi-squared distribution).
dof
A (non-negative) numeric
value giving the degrees of freedom.
In the code snippets below, x
is an OutlierIndex
object.
as.data.frame(x)
Coerces to a data.frame
.
N. Frerebeau
Other classes:
CompositionMatrix-class
,
LogRatio-class
,
LogicalMatrix-class
,
NumericMatrix-class