glm.object
Generalized Linear Model Object
Description
Classes of objects returned by fitting generalized linear model objects.
Value
| coefficients |
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.
|
| linear.predictors |
the linear fit, given by the product of the model matrix and the coefficients;
also the fitted.values from the final weighted least squares fit.
|
| fitted.values |
the fitted mean values, obtained by transforming linear.predictors
using the inverse link function.
|
| residuals |
the residuals from the final weighted least squares fit; also known as
workingresiduals, these are typically not interpretable without
rescaling by the weights.
|
| deviance |
up to a constant, minus twice the maximized log-likelihood.
Similar to the residual sum of squares.
|
| null.deviance |
the deviance corresponding to the model with no predictors.
|
| iter |
the number of IRLS iterations used to compute the estimates.
|
| family |
a 2 element character vector giving the name of the family,
the link function; mainly for printing purposes.
|
| weights |
the iterative weights from the final IRLS fit
|
| aic |
aic value computed by component aic of family function.
|
| prior.weights |
initial weights.
|
| df.null |
the number of degrees of freedom for null model.
|
| converged |
logical value if IRLS fit has converged.
|
| boundary |
logical value if fitted value on the boundary.
|
| data |
data frame, list or environment contains the model varaible.
|
| offset |
the value of argument offset used.
|
| control |
the value of argument control used.
|
| method |
the method name used for fit.
|
| na.action |
the na.action attribute of model.frame to handle missing values (NAs).
|
| xlevels |
the levels of factor used in fit.
|
The object will also have the components of an
lm object:
coefficients,
residuals,
fitted.values,
call,
terms,
effects,
R,
rank,
assign,
contrasts,
df.residual
R.assign,
assign.residuals,
qr,
model,
x and
y.
See
lm.object for more details.
Generation
This class of objects is returned by the glm function
to represent a fitted generalized linear model.
Class glm inherits from class lm, since it is fit by iterative reweighted
least squares; the object returned has all the components of a weighted least squares object.
Methods
Objects of this class have methods for the functions print,
plot, summary, anova, predict, fitted, drop1, add1,
amongst others.
Structure
The following components must be included in a legitimate glm object.
The residuals, fitted values, coefficients and effects 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.
See Also