search for: sigma_squar

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...

...X((xval^2),xprob) - (EX(xval,xprob))^2; doesn't work as I thought. I've looked intto FAQs and archives but my question is probably too simple. Can somebody tell me what's wrong on my example ? And one more question: when I'm plotting density: plot(x, dnorm(x,as.double(mu),as.double(sigma_square)), style ); on interval x I get relatively small number of probabilities. I've spent long time searching trough docs to find how to change it but didn't found it. So please tell me how. thanks for replies +-----------------------------------------------------------------------------+ | R...