Control for Misclassification Robust GLM Estimator

DESCRIPTION:

Allows users to set parameters for glmRob.

USAGE:

glmRob.misclass.control(mc.gamma = 0.01, mc.maxit = 30, mc.trc = F, mc.tol
= 0.001, mc.initial = NULL, ...)

OPTIONAL ARGUMENTS:

mc.gamma
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)