stats (version 3.3)

glm.control: Auxiliary for Controlling GLM Fitting

Description

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

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.

Value

• A list with components named as the arguments.

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.

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.

See Also

glm.fit, the fitting procedure used by glm.

Examples

### 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