glm.control {stats} | R Documentation |

## Auxiliary for Controlling GLM Fitting

### Description

Auxiliary function as user interface for `glm`

fitting.
Typically only used when calling `glm`

or `glm.fit`

.

### Usage

glm.control(epsilon = 1e-8, maxit = 25, trace = FALSE)

### Arguments

`epsilon` |
positive convergence tolerance *ε*;
the iterations converge when
*|dev - devold|/(|dev| + 0.1) < ε*. |

`maxit` |
integer giving the maximal number of IWLS iterations. |

`trace` |
logical indicating if output should be produced for each
iteration. |

### Details

If `epsilon`

is small, it is also used as the tolerance for 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 the arguments as components.

### 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

[Package

*stats* version 2.5.0

Index]