[R] nlme question

[Deepayan Sarkar]

On 11/17/05, Doran, Harold <HDoran at air.org> wrote:
> I think the authors are mistaken. Sigma is random error, and due to its
> randomness it cannot be systematically related to anything. It is this
> ind. assumption that allows for the likelihood to be expressed as
> described in Pinhiero and Bates p.62.

I think not. The issue is dependence between the _estimates_ of sigma,
tao, etc, and that may well be present. Presumably, if one can compute
the likelihood surface as a function of the 3 parameters, the hessian
at the MLE's would give the estimated covariance. However, I don't
think nlme does this.

A different approach you might want to consider is using mcmcsamp in
the lme4 package (or more precisely, the Matrix package) to get
samples from the joint posterior distribution. This is likely to be
better than the asymptotic normal approximation in any case.

Deepayan