Starting values slot

A long time ago (2005) Doug Bates wrote this (in the R-help list,
perhaps) with regard to specifying starting values for lmer:

for linear mixed models. The object "mer" is a mixed-effects
representation and the list "cv" is the control values. The only
thing that the C function "lmer_initial" does is set the initial
values of the relative precision matrices for the random effects.
These are the inverses of the variance-covariance matrices relative to
the variance of the per-observation noise term. They are stored
(upper triangle only) in a slot called "Omega" of the mer class (which
is contained in the lmer class).

Was this ever implemented? I don't see the Omega slot mentioned in the
mer-class documentation. I have a model that has been running for more
than 8 hours now (on a *very* fast machine, even) -- 2.6 million records
within two grouping factors containing 75,000 and 33,000 levels. (And
this version is just with a random sample of the full data.) When adding
fixed effects to the model, I'd like to avoid having to wait many hours
for it to finish, so I'd like to be able to speed things up by giving it
starting values from the previous version of the model. 

Can I use start=lm.previous at Omega, or is there another way to do this?

Thanks.

Stuart Luppescu wrote:

A long time ago (2005) Doug Bates wrote this (in the R-help list,
perhaps) with regard to specifying starting values for lmer:

for linear mixed models. The object "mer" is a mixed-effects
representation and the list "cv" is the control values. The only
thing that the C function "lmer_initial" does is set the initial
values of the relative precision matrices for the random effects.
These are the inverses of the variance-covariance matrices relative to
the variance of the per-observation noise term. They are stored
(upper triangle only) in a slot called "Omega" of the mer class (which
is contained in the lmer class).

Was this ever implemented? I don't see the Omega slot mentioned in the
mer-class documentation. I have a model that has been running for more
than 8 hours now (on a *very* fast machine, even) -- 2.6 million records
within two grouping factors containing 75,000 and 33,000 levels. (And
this version is just with a random sample of the full data.) When adding
fixed effects to the model, I'd like to avoid having to wait many hours
for it to finish, so I'd like to be able to speed things up by giving it
starting values from the previous version of the model.

Can I use start=lm.previous at Omega, or is there another way to do this?

Thanks.

?There's a function called ST2Omega() hidden in the namespace
(lme4:::ST2Omega), but reading the help for "lme4" it looks like you
should now just use the ST slot:

library(lme4)
fm0 <- lmer(Reaction ~ (Days|Subject), sleepstudy)
fm1 <- lmer(Reaction ~ Days + (Days|Subject), sleepstudy)
fm1B <- lmer(Reaction ~ Days + (Days|Subject), sleepstudy,
? ? ? ? ? ? start = fm0 at ST)
?? ?I'm a little out of my depth here ?