coxme.control {coxme}R Documentation

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.

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.

Value

a list of control parameters

Author(s)

Terry Therneau

See Also

coxme


[Package coxme version 2.0 Index]