tuning constant for the final estimate. The truncation
value for the likelihood equation is equal to `ufact *
sqrt(p) where
p is the rank of the design matrix. The larger
this value the more similar to the maximum likelihood estimate
the final estimate is. The smallest acceptable value
for
ufact is 1.1 .
bpar
cpar
tuning constant for the initial estimate. This is the
truncation value for the likelihood equation for the
initial estimate. It determines the starting point of the
iterative algorithm to calculate the final estimate.
trc
logical value. If
TRUE the number of the
current iteration is printed on the screen.
VALUE:
a list is returned, consisting of these parameters packaged to be
used by
glmRob(). The values for
glmRob.cubif.control()
can be supplied
directly in a call to
glmRob(). These values
are filtered through
glmRob.cubif.control()
inside
glmRob().
SEE ALSO:
.
EXAMPLES:
# The following are equivalent
<BR>
glmRob(formula, family, fit.method = 'cubif',
cubif.control=glmRob.cubif.control(epsilon=0.0001, maxit = 100))
glmRob(formula, family, fit.method = 'cubif', epsilon=0.0001, maxit = 100)