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<s-function-doc>
<s-topics>
   <s-topic>glmRob.object</s-topic>
</s-topics>

<s-title>
Robust Generalized Linear Model Objects 
</s-title>

<s-description>
These are objects of class <s-expression>glmRob</s-expression> which
represent the robust fit of a generalized linear regression model, as
estimated by <s-expression>glmRob()</s-expression>. 
</s-description>

<s-section name=" GENERATION">
This class of objects is returned from the
<s-expression>glmRob</s-expression> function.
</s-section>

<s-section name=" METHODS">

<s-expression>anova</s-expression>,
<s-expression>coefficients</s-expression>,
<s-expression>deviance</s-expression>,
<s-expression>fitted.values</s-expression>,
<s-expression>family</s-expression>, <s-expression>formula</s-expression>,
<s-expression>plot</s-expression>, <s-expression>print</s-expression>,
<s-expression>residuals</s-expression>,
<s-expression>summary</s-expression>. 
</s-section>

<s-section name=" STRUCTURE">
The following components must be included in a legitimate
<s-expression>"glmRob"</s-expression> object. Residuals, fitted values, and
coefficients should be extracted by the generic functions of the same name,
rather than by the <s-expression>"$"</s-expression> operator. The
<s-expression>family</s-expression> function returns the entire family
object used in the fitting, and <s-expression>deviance</s-expression> can
be used to extract the deviance of the fit. 
</s-section>

<s-value>
<s-return-component name="coefficients">
the coefficients of the <s-expression>linear.predictors</s-expression>,
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.
</s-return-component>

<s-return-component name="linear.predictors">
the linear fit, given by the product of the model matrix and the
coefficients.
</s-return-component>

<s-return-component name="fitted.values">
the fitted mean values, obtained by transforming
<s-expression>linear.predictors</s-expression> using the inverse link
function. 
</s-return-component>

<s-return-component name="residuals">
the residuals from the final fit; also known as working residuals, they are
typically not interpretable.
</s-return-component>

<s-return-component name="deviance">
up to a constant, minus twice the log-likelihood evaluated at the final
<s-expression>coefficients</s-expression>. Similar to the residual sum of
squares.
</s-return-component>

<s-return-component name="null.deviance">
the deviance corresponding to the model with no predictors. 
</s-return-component>

<s-return-component name="family">
a 3 element character vector giving the name of the family, the link and
the variance function.
</s-return-component>

<s-return-component name="rank">
the number of linearly independent columns in the model matrix.
</s-return-component>

<s-return-component name="df.residuals">
the number of degrees of freedom of the residuals.
</s-return-component>

<s-return-component name="call">
a copy of the call that produced the object.
</s-return-component>

<s-return-component name="assign">
the same as the <s-expression>assign</s-expression> component of an
<s-expression>"lm"</s-expression> object.
</s-return-component>

<s-return-component name="contrasts">
the same as the <s-expression>contrasts</s-expression> component of an <s-expression>"lm"</s-expression> object.  
</s-return-component>

<s-return-component name="terms">
the same as the <s-expression>terms</s-expression> component of an <s-expression>"lm"</s-expression> object.  
</s-return-component>

<s-return-component name="ni">
vector of the number of repetitions on the dependent variable. If the model
is poisson then <s-expression>ni</s-expression> is a vector of
<s-expression>1</s-expression>s.
</s-return-component>

<s-return-component name="weights">
weights from the final fit.
</s-return-component>

<s-return-component name="iter">
number of iterations used to compute the estimates.
</s-return-component>

<s-return-component name="y">
the dependent variable.
</s-return-component>

<s-return-component name="contrasts">
the same as the <s-expression>contrasts</s-expression> term of an
<s-expression>"lm"</s-expression> object. The object will also contain
other components related to the numerical fit that are not relevant for the
associated methods.  
</s-return-component>
</s-value>

<s-see>
<s-function name="glmRob.sgm">glmRob</s-function>.
</s-see>

<s-keywords>
<s-keyword>robust</s-keyword>
<s-keyword>regression</s-keyword>
<s-keyword>methods</s-keyword>
<s-keyword>models</s-keyword>
<s-keyword>librobust</s-keyword>
</s-keywords>

<s-docclass>
function
</s-docclass>

</s-function-doc>
