R help - Nov 2016 - nlme & VarIdent

Hello,

All the help I've read (including Pinheiro and Bates book, 'Mixed
Effects Models in S and S-PLUS') regarding how to fit a linear mixed-effects
model where variances change with a factor's levels indicates this is done
through the 'weights' argument to 'lme', using something like
'weights=varIdent(form=~v|g)' where 'v' is a variance covariate
and 'g' is the grouping factor whose strata have different random effect
variances.

My question: Suppose I have more than 1 variance covariate, say v1, ..., vk, and
I want _each_ of these to have variances that change with the levels of g giving
a total of k*nlevels(g) parameters (k*nlevels(g) - k allowing for
identifiability). How is this handled in the nlme package? A simple example
would be random slope and intercepts, _both_ of which have variances changing
with the levels of g. I haven't found any examples of this online or in
Pinheiro & Bates, and I haven't been able to figure this out using the
various varFunc/pdMat classes.

Help/advice would be greatly appreciated.

Thanks,

Paul Louisell
Statistical Specialist
Paul.Louisell at pw.utc.com
860-565-8104

Still, tomorrow's going to be another working day, and I'm trying to get
some rest.
That's all, I'm trying to get some rest. 
Paul Simon, "American Tune"

I suggest that you post instead on the r-sig-mixed-models list which
specializes in just this sort of query, and where you are therefore
likely to receive a quicker more authoritative response.


Cheers,
Bert



Bert Gunter

"The trouble with having an open mind is that people keep coming along
and sticking things into it."
-- Opus (aka Berkeley Breathed in his "Bloom County" comic strip )


On Thu, Nov 10, 2016 at 1:24 PM, Louisell, Paul T           PW
<Paul.Louisell at pw.utc.com> wrote:
> Hello,
>
> All the help I've read (including Pinheiro and Bates book, 'Mixed
Effects Models in S and S-PLUS') regarding how to fit a linear mixed-effects
model where variances change with a factor's levels indicates this is done
through the 'weights' argument to 'lme', using something like
'weights=varIdent(form=~v|g)' where 'v' is a variance covariate
and 'g' is the grouping factor whose strata have different random effect
variances.
>
> My question: Suppose I have more than 1 variance covariate, say v1, ...,
vk, and I want _each_ of these to have variances that change with the levels of
g giving a total of k*nlevels(g) parameters (k*nlevels(g) - k allowing for
identifiability). How is this handled in the nlme package? A simple example
would be random slope and intercepts, _both_ of which have variances changing
with the levels of g. I haven't found any examples of this online or in
Pinheiro & Bates, and I haven't been able to figure this out using the
various varFunc/pdMat classes.
>
> Help/advice would be greatly appreciated.
>
> Thanks,
>
> Paul Louisell
> Statistical Specialist
> Paul.Louisell at pw.utc.com
> 860-565-8104
>
> Still, tomorrow's going to be another working day, and I'm trying
to get some rest.
> That's all, I'm trying to get some rest.
> Paul Simon, "American Tune"
>
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