Thanks a lot for your suggestion.
I will try both way and see.
Keyan
On Mon, 2005-05-30 at 10:32 +0100, I M S White wrote:> The only way I know of in nlme is to transform Zu to Z1 u1 so that
> u1 ~ N(0, cI), which nlme can cope with. E.g. if A = PDP' is the
> spectral decomposition of A, take Z1=ZPD^{1/2}, u1 = D^{-1/2}P'u.
> Unfortunately Z1 is much less sparse than Z and in my experience
> this only works with small problems.
>
> The kinship package has a function lmekin which will do what you want. It
> uses ML but I reckon it could be easily modified to use REML. It does not
> make use of nlme, it just evaluates the log likelihood and passes it to a
> general purpose optimiser.
>
>
> On Thu, 26 May 2005, Keyan Zhao wrote:
>
> > Could anyone help with a linear mixed model fitting problem ?
> >
> > The model is :
> >
> > Y= Xp + Zu + e
> > where X, Z are known design matrix, p is fixed effect factor, u is
> > random effect, u~ (0, G) , e~(0,R)
> >
> > The main problem is , I want to fix the covariance matrix G to be a
> > constant times a known covariance matrix A, G = c*A (c is positive
> > constant, A is a predefined matrix with values manually set by me.
> >
> > I know the correlation option in lme function can specify some kind of
> > correlation. but only with the Construct function defined, not
whatever
> > ever form I want.
> >
> > Any good ideas of how to do this in R ?
> >
> > Thanks a lot in advance,
> >
> > Keyan Zhao
> > Computational Biology and Bioinformatics program
> > Univ of Southern California
> > Email: kzhao at usc.edu
> >
> =====================================> I.White
> University of Edinburgh
> Ashworth Laboratories, West Mains Road
> Edinburgh EH9 3JT
> Tel: 0131 650 5490 Fax: 0131 650 6564
> E-mail: iwhite at staffmail.ed.ac.uk
> ======================================