Auxillary function which packages the optional parameters of a
lmekin
fit as a single list.
1 2 3  lmekin.control(
optpar = list(method = "BFGS", control=list(reltol = 1e8)),
varinit=c(.02, .1, .8, 1.5)^2, corinit = c(0, .3))

optpar 
parameters passed forward to the 
varinit 
the default grid of starting values for variances, used if no

corinit 
the default grid of starting values for correlations. 
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 loglikelihood surface that is almost flat; a NewtonRaphson 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.
a list of control parameters
Terry Therneau
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