fsmult.object {fsdaR}

Description of fsmult.object Objects

Description

An object of class fsmult.object holds information about the result of a call to fsmult.

Value

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

outliers

kx1 vector containing the list of the k units declared as outliers or NULL if the sample is homogeneous.

loc

p-by-1 vector containing location of the data.

cov

p-by-p robust estimate of covariance matrix.

md

n-by-1 vector containing the estimates of the robust Mahalanobis distances (in squared units). This vector contains the distances of each observation from the location of the data, relative to the scatter matrix cov.

mmd

(n-init)-by-2 matrix. 1st col is the forward search index; 2nd col is the value of minimum Mahalanobis Distance in each step of the fwd search.

Un

(n-init)-by-11 matrix which contains the unit(s) included in the subset at each step of the fwd search. REMARK: in every step the new subset is compared with the old subset. Un contains the unit(s) present in the new subset but not in the old one. Un[1 ,2] for example contains the unit included in step init+1. Un[end, 2] contains the units included in the final step of the search.

nout

2 x 5 matrix containing the number of times mdr went out of particular quantiles. First row contains quantiles 1 99 99.9 99.99 99.999. Second row contains the frequency distribution. It is NULL if bonflev threshold is used.

constr

This output is produced only if the search found at a certain step is a non singular matrix X. In this case the search run in a constrained mode, that is including the units which produced a singular matrix in the last n-constr steps. out.constr is a vector which contains the list of units which produced a singular X matrix.

X

the data matrix X

The object has class "fsmult".

Examples

## Not run:   
    data(hbk, package="robustbase")
    (out <- fsmult(hbk[,1:3]))
    class(out)
    summary(out)

## End(Not run)