Aah. From your model description, you are more interested in the
covariance structure of the random effects, rather than the residuals.
You will then need to use the pdSymm class in the specification of the
random effects. See Pinheiro and Bates pp 157-166.
Cheers,
Simon.
On 06/07/12 11:43, Marcio wrote:
Hi folks,
I was wondering how to run a mixed models approach to analyze a linear
regression with a user-defined covariance structure.
I have my model
y = xa +zb +e and
b ~ N (0, C*sigma_square). (and a is a fixed effects)
I would like to provide R the C (variance-covariance) matrix
I can easily provide an example, but at this point I am first trying to know
what is the best package the allows an unstructured covariance matrix.
I was trying the function lme in the package nlme but I didn't have success
in the defining the option "correlation"
Thanks
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