Auxillary function which packages the optional parameters of a
lmekin fit as a single list.
lmekin.control(
optpar = list(method = "BFGS", control=list(reltol = 1e-8)),
varinit=c(.02, .1, .8, 1.5)^2, corinit = c(0, .3))a list of control parameters
parameters passed forward to the optim routine.
the default grid of starting values for variances, used if no
vinit argument is supplied in the lmekin call.
the default grid of starting values for correlations.
Terry Therneau
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.
lmekin