Generalized Linear Model Object

DESCRIPTION:

Classes of objects returned by fitting generalized linear model objects.

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. The class of gam objects, on the other hand, inherit from class glm.

METHODS:

Objects of this class have methods for the functions print, plot , summary, anova, predict, fitted, drop1, add1, and step, 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.

ARGUMENTS:

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 3 element character vector giving the name of the family, the link and the variance function; mainly for printing purposes.
weights
the iterative weights from the final IRLS fit
The object will also have the components of an lm object: coefficients, residuals, fitted.values, call, terms and some others involving the numerical fit. See lm.object.

SEE ALSO:

, , .