glm model, without computing the model matrix or the response vector.
glm.fit(x, y, w, start, offset, family, maxit, epsilon, trace,
null.dev, qr, ...)
family$initialize.
binomial (default is
gaussian).
TRUE iterations details are printed during execution.
FALSE.
TRUE, the
qr decomposition of
x*sqrt(w)
is returned with the fit; default is
FALSE.
glm object.
In particular, some of the extractor functions like
summary.glm
produce appropriate output.
This function is useful for simulations or bootstrapping, where you use
the same data frame over and over again. Using
glm.fit for bootstrapping
saves a large amount of computational time, since it only fits a
glm model
and does not create the model matrix. Thus, no formula needs to be
specified as an argument. The
glm.fit function is called
internally by
glm to do the actual model fitting.
The
glm.fit function is the work-horse for
glm, and is named as
the default
method in the definition of
glm.
It receives
x and
y data rather than a formula, but
still uses the
family object to define the IRLS steps.
Users can write their own versions of
glm.fit, and pass the name of their
function via the
method argument to
glm.
Care should be taken to include as many of the arguments as feasible,
but definitely the
... argument, which will absorb any additional
arguments given in the call from
glm.
The name of the method can optionally be passed as a
"method"
attribute of the family argument.
This allows users to define, say, a
cox family, with
"method"
attribute
"cox.fit";
glm will automatically look for a fitting
function
cox.fit and use it instead of
glm.fit.
glm(Times ~ Dose + Age, family = "cox", method = "glm.fit.cox")