methods
for class glmbb or summary.glmbb objects.## S3 method for class 'glmbb':
summary(object, cutoff, \dots)## S3 method for class 'summary.glmbb':
print(x, digits = max(3, getOption("digits") - 3),
...)
"glmbb", usually, a result of a
call to glmbb.cutoff.
This argument may be omitted, in which case object$cutoff is
used."summary.glmbb", usually, a result of a
call to summary.glmbb.summary.glmbb returns an object of class "summary.glmbb", a
list with componentscutoff argument to the call to glmbb
that produced object.cutoff argument to the call to
summary.glmbb.results$criterion.criterion denote the vector of criterion (AIC, BIC, or AICc)
values for all of the models evaluated in the search. Those with
criterion value greater than min(criterion) + cutoff are tossed. We also define a vector weight by
w <- exp(- criterion / 2)
weight <- w / sum(w)
except that it is calculated differently to avoid overflow.
These are so-called Akaike weights. They may or may not provide some
guide as to how to deal with these models. For more see Burnham and
Anderson (2002).
## For examples see those in help(glmbb)Run the code above in your browser using DataLab