glm.control {stats} | R Documentation |
Auxiliary function for glm
fitting.
Typically only used internally by glm.fit
, but may be
used to construct a control
argument to either function.
glm.control(epsilon = 1e-8, maxit = 25, trace = FALSE)
epsilon |
positive convergence tolerance |
maxit |
integer giving the maximal number of IWLS iterations. |
trace |
logical indicating if output should be produced for each iteration. |
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.
A list with components named as the arguments.
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
.
### 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