fsr.object {fsdaR}

Description of fsr Objects

Description

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

Value

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

beta

p-by-1 vector containing the estimated regression parameters (in step n-k).

scale

scalar containing the estimate of the scale (sigma).

residuals

residuals.

fittedvalues

fitted values.

outliers

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

mdr

(n-init) x 2 matrix 1st col = fwd search index, 2nd col = value of minimum deletion residual in each step of the fwd search

Un

(n-init) x 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.

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

y

the response vector y

The object has class "fsr".

Examples

## Not run:   
    data(hbk, package="robustbase")
    (out <- fsreg(Y~., data=hbk, method="FS"))
    class(out)
    summary(out)

## End(Not run)