The class Cov represents an estimate of the
multivariate location and scatter of a data set. The objects of class Cov
contain the classical estimates and serve as base for deriving other
estimates, i.e. different types of robust estimates.
Objects can be created by calls of the form new("Cov", ...),
but the usual way of creating Cov objects is a call to the function
Cov which serves as a constructor.
call:Object of class "language"
cov:covariance matrix
center:location
n.obs:number of observations used for the computation of the estimates
mah:mahalanobis distances
det:determinant
flag:flags (FALSE if suspected an outlier)
method:a character string describing the method used to compute the estimate: "Classic"
singularity:a list with singularity information for the
covariance matrix (or NULL of not singular)
X:data
signature(obj = "Cov"): location vector
signature(obj = "Cov"): covariance matrix
signature(obj = "Cov"): correlation matrix
signature(obj = "Cov"): data frame
signature(obj = "Cov"): distances
signature(obj = "Cov"): Computes and returns
the eigenvalues of the covariance matrix
signature(obj = "Cov"): Computes and returns
the determinant of the covariance matrix (or 0 if the covariance matrix is singular)
signature(obj = "Cov"): Computes and returns
the shape matrix corresponding to the covariance matrix (i.e. the covariance matrix scaled to have determinant =1)
signature(obj = "Cov"): Flags observations as outliers if the corresponding mahalanobis distance is larger then qchisq(prob, p) where prob defaults to 0.975.
signature(obj = "Cov"): returns TRUE by default. If necessary, the robust
classes will override
signature(x = "Cov"): plot the object
signature(object = "Cov"): display the object
signature(object = "Cov"): calculate summary information
Valentin Todorov valentin.todorov@chello.at
Todorov V & Filzmoser P (2009), An Object Oriented Framework for Robust Multivariate Analysis. Journal of Statistical Software, 32(3), 1--47. tools:::Rd_expr_doi("10.18637/jss.v032.i03").