R: Auxillary parameters for controlling lmekin fits.

lmekin.control {coxme} | R Documentation

## Auxillary parameters for controlling lmekin fits.

### Description

Auxillary function which packages the optional parameters of a `lmekin` fit as a single list.

### Usage

    lmekin.control(
    optpar = list(method = "BFGS", control=list(reltol = 1e-8)),
    varinit=c(.02, .1, .8, 1.5)^2, corinit = c(0, .3))

### Arguments

`optpar` | parameters passed forward to the `optim` routine.
`varinit` | the default grid of starting values for variances, used if no `vinit` argument is supplied in the `lmekin` call.
`corinit` | the default grid of starting values for correlations.

### Details

The main flow of `lmekin` is to use the `optim` routine to find the best values for the variance parameters. For any given trial value of the variance parameters, a subsidiary computation maximizes the likelihood to select the regression coefficients beta (fixed) and b (random).

If no starting values are supplied for the variances of the random effects then a grid search is performed to select initial values for the main iteration loop. The variances and correlations are all scaled by sigma^2, making these starting estimates scale free, e.g., replacing y by 10*y in a data set will change sigma but not the internal representation of any other variance parameters. Because we use the log(variance) as our iteration scale the 0–.001 portion of the variance scale is stretched out giving a log-likelihood surface that is almost flat; a Newton-Raphson iteration starting at log(.2) may have log(.0001) as its next guess and get stuck there, never finding a true maximum that lies in the range of .01 to .05. Corrleation paramters seem to need fewer starting points.

### Value

a list of control parameters

### Author(s)

Terry Therneau

### See Also

`lmekin`

[Package coxme version 2.2-7 Index]