The object itself is basically a list
with the following
components:
locp-by-1 vector containing MM estimate of location.
shapep-by-p matrix with MM estimate of the shape matrix.
covmatrix with MM estimate of the covariance matrix.
Remark: covariance = auxscale^2 * shape
.
weightsA vector containing the estimates of the weights.
outliersA vector containing the list of the units declared
as outliers using confidence level specified in input scalar
conflev
.
SlocA vector with S estimate of location.
SshapeA matrix with S estimate of the shape matrix.
ScovA matrix with S estimate of the covariance matrix.
auxscaleS estimate of the scale.
mdn-by-1 vector containing the estimates of the robust
Mahalanobis distances (in squared units).
conflevConfidence level that was used to declare outliers.
Xthe data matrix X
The object has class "mmmult".