An object of class sreg.object
holds information about
the result of a call to fsreg
.
The object itself is basically a list
with the following
components:
p-by-1 vector containing the estimated regression parameters (in step n-k).
scalar containing the estimate of the scale (sigma).
p x 1 vector containing the units forming best subset associated with S estimate of regression coefficient.
residuals.
fitted values.
kx1 vector containing the list of the k units declared as outliers or NULL if the sample is homogeneous.
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
Number of subsets wihtout full rank. Notice that
singsub > 0.1*(number of subsamples)
produces a warning
n x 1 vector containing the estimates of the weights
Specifies the rho function which has been used to weight the residuals.
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.
the data matrix X
the response vector y
The object has class "sreg".
# NOT RUN {
(out <- fsreg(Y~., data=hbk, method="S"))
class(out)
summary(out)
# }
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