Auxiliary function as user interface for brglm
fitting. Typically only used when calling brglm or brglm.fit.
brglm.control(br.epsilon = 1e-08, br.maxit = 100, br.trace=FALSE,
br.consts = NULL, ...)positive convergence tolerance for the iteration
described in brglm.fit.
integer giving the maximum number of iterations for
the iteration in brglm.fit.
logical indicating if output should be prooduced for each iteration.
a (small) positive constant or a vector of such.
further arguments passed to or from other methods.
A list with the arguments as components.
If br.trace=TRUE then for each iteration the iteration number
and the current value of the modified scores is
cat'ed. If br.consts is specified then br.consts
is added to the original binomial counts and 2*br.consts. Then
the model is fitted to the adjusted data to provide starting values
for the iteration in brglm.fit. If br.consts = NULL
(default) then brglm.fit adjusts the responses and totals by
"number of parameters"/"number of observations" and twice that, respectively.
Kosmidis I. and Firth D. (2021). Jeffreys-prior penalty, finiteness and shrinkage in binomial-response generalized linear models. Biometrika, 108, 71--82.
Kosmidis, I. (2007). Bias reduction in exponential family nonlinear models. PhD Thesis, Department of Statistics, University of Warwick.