Description Value Methods Structure See Also
These are objects of class glmRob
which represent the robust fit of a generalized linear regression model, as estimated by glmRob()
.
coefficients 
the coefficients of the 
linear.predictors 
the linear fit, given by the product of the model matrix and the coefficients. 
fitted.values 
the fitted mean values, obtained by transforming

residuals 
the residuals from the final fit; also known as working residuals, they are typically not interpretable. 
deviance 
up to a constant, minus twice the loglikelihood evaluated at the final

null.deviance 
the deviance corresponding to the model with no predictors. 
family 
a 3 element character vector giving the name of the family, the link and the variance function. 
rank 
the number of linearly independent columns in the model matrix. 
df.residuals 
the number of degrees of freedom of the residuals. 
call 
a copy of the call that produced the object. 
assign 
the same as the 
contrasts 
the same as the 
terms 
the same as the 
ni 
vector of the number of repetitions on the dependent variable. If the model
is poisson then 
weights 
weights from the final fit. 
iter 
number of iterations used to compute the estimates. 
y 
the dependent variable. 
contrasts 
the same as the 
anova
,
coefficients
,
deviance
,
fitted.values
,
family
, formula
,
plot
, print
,
residuals
,
summary
.
The following components must be included in a legitimate
"glmRob"
object. Residuals, fitted values, and
coefficients should be extracted by the generic functions of the same name,
rather than by the "\$"
operator. The
family
function returns the entire family
object used in the fitting, and deviance
can
be used to extract the deviance of the fit.
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