coxme.control: Auxillary parameters for controlling coxme fits.
Description
Auxillary function which packages the optional parameters of a
coxme fit as a single list.Usage
coxme.control(eps = 1e-08, toler.chol = .Machine$double.eps^0.75,
iter.max = 20, inner.iter = 5, sparse.calc = NULL,
optpar = list(method = "BFGS", control=list(reltol = 1e-5)))
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
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.
Value
- a list of control parameters
Details
The main flow of coxme is to use the optim routine to
find the best values for the variance parameters. For any given trial
value of the variance parameters, an inner loop maximizes the partial
likelihood to select the regression coefficients beta (fixed) and b
(random). Within this loop cholesky decomposition is used. It is
critical that the convergence criteria of inner loops be less than
outer ones, thus toler.chol < eps < reltol.