fsdaR (version 0.9-0)

smulteda.object: Description of smulteda.object Objects

Description

An object of class smulteda.object holds information about the result of a call to smult with monitoring=TRUE.

Value

The object itself is basically a list with the following components:

Loc

length(bdp)-by-p matrix containing S estimate of location for each value of bdp.

Shape

p-by-p-by-length(bdp) 3D array containing robust estimate of the shape for each value of bdp. Remark: det|shape|=1.

Scale

length(bdp) vector containing robust estimate of the scale for each value of bdp.

Cov

p-by-p-by-length(bdp) 3D array containing robust estimate of covariance matrix for each value of bdp. Note that scale(i)^2 * shape[,,i] = robust estimate of covariance matrix.

Bs

(p+1)-by-length(bdp) matrix containing the units forming best subset for each value of bdp.

MAL

n-by-length(bdp) matrix containing the estimates of the robust Mahalanobis distances (in squared units) for each value of bdp.

Outliers

n-by-length(bdp) matrix containing flags for the outliers. Boolean matrix containing the list of the units declared as outliers for each value of bdp using confidence level specified in input scalar conflev

Weights

n x length(bdp) matrix containing the weights for each value of bdp.

conflev

Confidence level that was used to declare outliers.

singsub

Number of subsets without full rank. Notice that singsub > 0.1*(number of subsamples) produces a warning.

bdp

vector which contains the values of bdp which have been used.

X

the data matrix X.

The object has class "smulteda".

Examples

if (FALSE) {
    data(hbk, package="robustbase")
    (out <- smult(hbk[,1:3], monitoring=TRUE))
    class(out)
    summary(out)
}