These are objects of class glmRob which represent the robust fit of a generalized linear regression model, as estimated by glmRob().
the coefficients of the linear.predictors,
which multiply the columns of the model matrix. The names of the
coefficients are the names of the single-degree-of-freedom effects (the
columns of the model matrix). If the model is over-determined there will be
missing values in the coefficients corresponding to inestimable
coefficients.
the linear fit, given by the product of the model matrix and the coefficients.
the fitted mean values, obtained by transforming
linear.predictors using the inverse link
function.
the residuals from the final fit; also known as working residuals, they are typically not interpretable.
up to a constant, minus twice the log-likelihood evaluated at the final
coefficients. Similar to the residual sum of
squares.
the deviance corresponding to the model with no predictors.
a 3 element character vector giving the name of the family, the link and the variance function.
the number of linearly independent columns in the model matrix.
the number of degrees of freedom of the residuals.
a copy of the call that produced the object.
the same as the assign component of an
"lm" object.
the same as the contrasts component of an "lm" object.
the same as the terms component of an "lm" object.
vector of the number of repetitions on the dependent variable. If the model
is poisson then ni is a vector of
1s.
weights from the final fit.
number of iterations used to compute the estimates.
the dependent variable.
the same as the contrasts term of an
"lm" object. The object will also contain
other components related to the numerical fit that are not relevant for the
associated methods.
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.