[S] maxit in step.glm

Lorenz Gygax (lgygax@amath.unizh.ch)
Mon, 9 Mar 1998 13:55:21 +0100 (MET)

Dear all,

I am currently helping someone to fit a logistic regression to a rather
big data set (about 15'000 cases and a 100 variables). Often, the default
number of iterations (10) is not enough to get convergence in the glm
algorithm. Thus we do:

glm.control (maxit = 50)
our.fit <- glm (Y ~ (lengthy list of variables), family = binomial)

This allows us to get a fit. Now we would like to use step.glm to reduce
the variables, but step.glm does maximally 10 iterations and not the
number of iterations given with maxit. Is there any way to force step.glm
to increase the number of iterations?

I hope I have been specific enough. Thanks for thoughts and help!


			Lorenz Gygax

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