Robust Linear Model Objects -- Bounded Influence Estimator
DESCRIPTION:
These are objects of class
lmRobBI which represent the robust fit of
a linear regression model, as estimated by
lmRobBI() function.
GENERATION:
This class of objects is returned from the
lmRobBI function.
METHODS:
coefficients
,
fitted.values,
formula,
labels,
plot,
print
,
residuals,
summary.
STRUCTURE:
The following components must be included in a legitimate
"lmRobBI"
object:
VALUE:
- coefficients
-
vector of coefficients for the robust regression.
- scale
-
the bounded influence estimate of scale parameter.
- residuals
-
the residual vector corresponding to the estimates returned in
coefficients
.
- fitted.values
-
the fitted values corresponding to the estimates returned in
coefficients.
- O.weights
-
the optimal weights used by the bounded influence estimator.
- cov
-
the estimated covariance matrix of the estimates in
coefficients.
- iter.weight
-
the number of iterations used in the nonlinear algorithm for computing
the optimal weights.
- iter.coef
-
the number of iterations used in the nonlinear algorithm for computing
the coefficient estimates.
- rank
-
the rank of the design matrix
x.
- call
-
an image of the call that produced the object, but with the arguments all
named and with the actual formula included as the
formula argument.
- assign
-
the same as the
assign component of an
"lm" object.
- contrasts
-
the same as the
contrasts component of an
"lm" object.
- terms
-
the same as the
terms component of an
"lm" object.
SEE ALSO:
.