Hi,
I'll briefly describe the situation. An EM algorithm is being implemented in
order to cluster observations into components of a mixture of mixed effects
models.  It was our hope to use the lme() or lmer() function in the M-step
to easily find weighted-ML parameter estimates.  Unfortunately, the mixed
models are often quite complex including serial correlation structures etc.


Weighted-ML estimates of certain parameters (such as the correlation
parameters) does not seem likely in closed form or by using lme()/lmer().
 Due to the weighted-likelihood function, it does not seem appropriate to
simply use a weighted-least squares approach.  Are appropriate numeric
approaches available? Has anyone had experience with mixtures of mixed
models?

any help would be greatly appreciated,

Harlan

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