glm.control

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Auxiliary for Controlling GLM Fitting

Auxiliary function for glm fitting. Typically only used internally by glm.fit, but may be used to construct a control argument to either function.

Keywords
models, optimize
Usage
glm.control(epsilon = 1e-8, maxit = 25, trace = FALSE)
Arguments
epsilon
positive convergence tolerance $\epsilon$; the iterations converge when $|dev - dev_{old}|/(|dev| + 0.1) < \epsilon$.
maxit
integer giving the maximal number of IWLS iterations.
trace
logical indicating if output should be produced for each iteration.
Details

The control argument of glm is by default passed to the control argument of glm.fit, which uses its elements as arguments to glm.control: the latter provides defaults and sanity checking.

If epsilon is small (less than $10^{-10}$) it is also used as the tolerance for the detection of collinearity in the least squares solution.

When trace is true, calls to cat produce the output for each IWLS iteration. Hence, options(digits = *) can be used to increase the precision, see the example.

Value

• A list with components named as the arguments.

References

Hastie, T. J. and Pregibon, D. (1992) Generalized linear models. Chapter 6 of Statistical Models in S eds J. M. Chambers and T. J. Hastie, Wadsworth & Brooks/Cole.

glm.fit, the fitting procedure used by glm.
library(stats) ### A variation on example(glm) : ## Annette Dobson's example ... counts <- c(18,17,15,20,10,20,25,13,12) outcome <- gl(3,1,9) treatment <- gl(3,3) oo <- options(digits = 12) # to see more when tracing : glm.D93X <- glm(counts ~ outcome + treatment, family = poisson(), trace = TRUE, epsilon = 1e-14) options(oo) coef(glm.D93X) # the last two are closer to 0 than in ?glm's glm.D93