Usage
coxme.control(eps = 1e-08, toler.chol = .Machine$double.eps^0.75,
iter.max = 20, inner.iter = Quote(max(4, fit0$iter+1)),
sparse.calc = NULL,
optpar = list(method = "BFGS", control=list(reltol = 1e-5)),
refine.df=4, refine.detail=FALSE)
Arguments
eps
convergence criteria for the partial likelihood
toler.chol
tolerance for the underlying Cholesky decomposition. This is used
to detect singularity (redundant variables).
iter.max
maximum number of iterations for the final fit
inner.iter
number of iterations for the `inner loop' fits, i.e. when the
partial likelihood is the objective function of optim.
The default is to use one more iteration than the baseline coxph
model fit0. The baseline model con
sparse.calc
choice of method 1 or 2 for a particular portion of the
calculation. This can have an effect on run time for problems with
thousands of random effects.
optpar
parameters passed forward to the optim routine.
refine.df
the degrees of freedom for the t-distribution
used to draw random samples
for the refine.n option
refine.detail
this option is mostly for debugging. If TRUE
then an extra component refine.detail will be present in
the output which contains intermediate variables from the
iterative refinement calculation.