Control for Bounded Influence Robust GLM Estimator

DESCRIPTION:

Allows users to set parameters for glmRob.

USAGE:

glmRob.cubif.control(epsilon = 0.001, maxit = 50, bpar = 2, cpar = 1.5, trc
= F, ...)

OPTIONAL ARGUMENTS:

epsilon
convergence threshold for the parameters.
maxit
maximum number of iterations.
ufact
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)