[R] Mixed Models providing a correlation structure.

Simon Blomberg s.blomberg1 at uq.edu.au
Fri Jul 6 06:36:49 CEST 2012

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.



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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Simon Blomberg, BSc (Hons), PhD, MAppStat, AStat.
Lecturer and Consultant Statistician
School of Biological Sciences
The University of Queensland
St. Lucia Queensland 4072
T: +61 7 3365 2506
email: S.Blomberg1_at_uq.edu.au

1.  I will NOT analyse your data for you.
2.  Your deadline is your problem.

Statistics is the grammar of science - Karl Pearson.

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