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 |
varinit |
the default grid of starting values for variances, used if no
|
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