Minimum Covariance Determinant Object

DESCRIPTION:

These are objects of class mcd They represent robust estimates of multivariate location and scatter, obtained from the minimum covariance determinant estimator (Rousseeuw, 1985).

GENERATION:

This class of objects is returned from the cov.mcd function.

METHODS:

The "mcd" class of objects has methods for the following generic functions:

plot, print, summary.

STRUCTURE:

The following components must be included in a legitimate mcd object.

VALUE:

cov
the robust covariance matrix obtained by reweighting. (If the raw MCD is singular, it is given here.)
center
the robust location estimate of the data, obtained by reweighting. (If the raw MCD is singular, its center is given here.)
n.obs
the number of data observations (without missing values).
cor
the estimated correlation matrix for the data. This is only returned if the input cor is TRUE.
method
a character string that contains information about the method and about singular subsamples (if any).
quan
the number of observations that have determined the minimum covariance determinant estimator. The default is floor((n+p+1)/2), where n is the number of observations and p the number of variables.
raw.cov
the raw MCD covariance matrix.
raw.center
the raw MCD location of the data.
raw.objective
the determinant of the raw MCD covariance matrix.
mcd.wt
weights based on the estimated covariance matrix and the estimated location of the data.
X
same as the input data of cov.mcd.default or the data matrix.
model
optionally the model frame, if model=TRUE (in cov.mcd.formula).
x
optionally the model matrix, if x=TRUE (in cov.mcd.formula).

SEE ALSO:

, .