A S4 class to store results from performing outlier detection in an ICS context.
Objects can be created by calls of the form new("icsOut", ...). But usually objects are created by the function ics.outlier.
outliers:Object of class "integer". A vector containing ones for outliers and zeros for non outliers.
ics.distances:Object of class "numeric". Vector giving the squared ICS distances of the observations from the invariant coordinates centered with the location estimate specified in S1.
ics.dist.cutoff:Object of class "numeric". The cut-off for the distances to decide if an observation is outlying or not.
level.dist:Object of class "numeric". The level for deciding upon the cut-off value for the ICS distances.
level.test:Object of class "numeric". The inital level for selecting the invariant coordinates.
method:Object of class "character". Name of the method used to decide upon the number of ICS components.
index:Object of class "numeric". Vector giving the indices of the ICS components selected.
test:Object of class "character". The name of the normality test as specified in the function call.
criterion:Object of class "numeric". Vector giving the marginal levels for the components selection.
adjust:Object of class "logical". Wether the initial level used to decide upon the number of components has been adjusted for multiple testing or not.
type:Object of class "character". Currently always the string "smallprop".
mDist:Object of class "integer". Number of simulations performed to decide upon the cut-off for the ICS distances.
mEig:Object of class "integer". Number of simulations performed for selecting the ICS components based on simulations.
S1name:Object of class "character". Name of S1 in the original ics2 object.
S2name:Object of class "character". Name of S2 in the original ics2 object.
For this class the following generic functions are available: print.icsOut, summary.icsOut and plot.ics
Aurore Archimbaud and Klaus Nordhausen
ics.outlier