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 -- View this message in context: http://r.789695.n4.nabble.com/Mixed-Models-providing-a-correlation-structure-tp4635569.html Sent from the R help mailing list archive at Nabble.com. ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
