step(object, scope, scale = 0, direction = c("both", "backward", "forward"), trace = 1, keep = NULL, steps = 1000, k = 2, ...)"lm" and "glm").
This is used as the initial model in the stepwise search.
upper and lower, both formulae. See the
details for how to specify the formulae and how they are used.
lm, aov and
glm models. The default value, 0, indicates
the scale should be estimated: see extractAIC.
"both",
"backward", or "forward", with a default of "both".
If the scope argument is missing the default for
direction is "backward". Values can be abbreviated.
step.
Larger values may give more detailed information.
AIC statistic, and whose output is arbitrary.
Typically keep will select a subset of the components of
the object and return them. The default is not to keep anything.
k = 2 gives the genuine AIC: k = log(n) is sometimes
referred to as BIC or SBC.
extractAIC.
"anova" component corresponding to the
steps taken in the search, as well as a "keep" component if the
keep= argument was supplied in the call. The
"Resid. Dev" column of the analysis of deviance table refers
to a constant minus twice the maximized log likelihood: it will be a
deviance only in cases where a saturated model is well-defined
(thus excluding lm, aov and survreg fits,
for example).
na.action = na.omit is used. We suggest you remove the
missing values first. Calls to the function nobs are used to check that the
number of observations involved in the fitting process remains unchanged.step uses add1 and drop1
repeatedly; it will work for any method for which they work, and that
is determined by having a valid method for extractAIC.
When the additive constant can be chosen so that AIC is equal to
Mallows' $Cp$, this is done and the tables are labelled
appropriately. The set of models searched is determined by the scope argument.
The right-hand-side of its lower component is always included
in the model, and right-hand-side of the model is included in the
upper component. If scope is a single formula, it
specifies the upper component, and the lower model is
empty. If scope is missing, the initial model is used as the
upper model.
Models specified by scope can be templates to update
object as used by update.formula. So using
. in a scope formula means ‘what is
already there’, with .^2 indicating all interactions of
existing terms.
There is a potential problem in using glm fits with a
variable scale, as in that case the deviance is not simply
related to the maximized log-likelihood. The "glm" method for
function extractAIC makes the
appropriate adjustment for a gaussian family, but may need to be
amended for other cases. (The binomial and poisson
families have fixed scale by default and do not correspond
to a particular maximum-likelihood problem for variable scale.)
Venables, W. N. and Ripley, B. D. (2002) Modern Applied Statistics with S. New York: Springer (4th ed).
stepAIC in \href{https://CRAN.R-project.org/package=#1}{\pkg{#1}}MASSMASS, add1,
drop1