a real number between 0 and 1 that represents the probability of
misclassification of a response variable.
mc.maxit
maximum number of iterations.
mc.trc
a logical value indicating whether a trace of the current parameter values
is printed to the screen while the algorithm iterates.
mc.tol
convergence threshold.
mc.initial
a vector of initial values to start the iterations. If ommited, the
coeficients resulting from a non-robust glm fit are used.
VALUE:
a list is returned, consisting of these parameters packaged to be used by
glmRob()
. The values for
glmRob.misclass.control()
can be supplied
directly in a call to
glmRob(). These values
are filtered through
glmRob.misclass.control()
inside
glmRob().
SEE ALSO:
.
EXAMPLES:
# The following are equivalent
glmRob(formula, family, fit.method = 'misclass',
misclass.control=glmRob.misclass.control(mc.trace = T)
glmRob(formula, family, fit.method = 'misclass', mc.maxit = 50, mc.tol =
1e-8)