Hello Ravi, have you considered the SUR method proposed by Zellner? An implementation of it is provided in CRAN-package 'systemfit' (see ?systemfit for more information).
Best, Bernhard > >Suppose I have a multivariate response Y (n x k) obtained at a set of >predictors X (n x p). I would like to perform a linear >regression taking >into consideration the covariance structure of Y within each >unit - this >would be represented by a specified matrix V (k x k), assumed >to be the same >across units. How do I use "lm" to do this? > > > >One approach that I was thinking of is as follows: > > > >Flatten Y to a vector, say, Yvec (n*k x 1). Create Xvec (n*k, >p*k) such >that it is made up of block matrices Bij (k x k), where Bij is >a diagonal >matrix with X_ij as the diagonal (i = 1,.n, and j = 1,.,p). >Now I can use >"lm" in a univariate mode to regress Yvec against Xvec, with covariance >matrix Vvec (n*k x n*k). Vvec is a block-diagonal matrix with >blocks of V >along the diagonal. This seems like a valid approach, but I >still don't >know how to specify the covariance structure to do weighted >least squares. > > > >Any help is appreciated. > > > >Best, > >Ravi. > > > >--------------------------------------------------------------- >------------- >------- > >Ravi Varadhan, Ph.D. > >Assistant Professor, The Center on Aging and Health > >Division of Geriatric Medicine and Gerontology > >Johns Hopkins University > >Ph: (410) 502-2619 > >Fax: (410) 614-9625 > >Email: [EMAIL PROTECTED] > >Webpage: >http://www.jhsph.edu/agingandhealth/People/Faculty/Varadhan.html > > > >--------------------------------------------------------------- >------------- >-------- > > > > > [[alternative HTML version deleted]] > >______________________________________________ >R-help@stat.math.ethz.ch 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. > ***************************************************************** Confidentiality Note: The information contained in this mess...{{dropped}} ______________________________________________ R-help@stat.math.ethz.ch 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.
