sreg.object {fsdaR}

Description of sreg Objects

Description

An object of class sreg.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).

bs

p x 1 vector containing the units forming best subset associated with S estimate of regression coefficient.

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.

conflev

Confidence level which is used to declare units as outliers. Usually conflev=0.95, 0.975, 0.99 (individual alpha) or conflev=1-0.05/n, 1-0.025/n, 1-0.01/n (simultaneous alpha). Default value is 0.975

singsub

Number of subsets wihtout full rank. Notice that singsub > 0.1*(number of subsamples) produces a warning

weights

n x 1 vector containing the estimates of the weights

rhofunc

Specifies the rho function which has been used to weight the residuals.

rhofuncparam

Vector which contains the additional parameters for the specified rho function which has been used. For hyperbolic rho function the value of k =sup CVC. For Hampel rho function the parameters a, b and c.

X

the data matrix X

y

the response vector y

The object has class "sreg".

Examples

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

## End(Not run)