[R-sig-ME] Non-diagonal sampling covariance with lme4

[Ben Bolker]

... and for more nuts and bolts about how to modify X (and possibly Z?) and
feed it back into the lme4 machinery, see ?modular ...

On Mon, Nov 17, 2014 at 11:07 AM, Douglas Bates <bates at stat.wisc.edu> wrote:

> You can "pre-whiten" the response and the model matrices by multiplying by
> either the right or left inverse Cholesky factor of V.  (I always need to
> write out the equations before i can determine if I should use the left or
> the right factor.)
>
> On Mon Nov 17 2014 at 9:11:45 AM Asaf Weinstein <
> asafw.at.wharton at gmail.com>
> wrote:
>
> > Hi all,
> >
> > I would like to obtain ML (or REML) estimates for theta, beta, sigsq in
> >
> > Y|B=b ~ N( Zb + Xbeta, sigsq*V )
> > B ~ N( 0,Sigma(theta) )
> >
> > where V is a known covariance matrix. lmer() does exactly that for V=I_n
> > (the n-by-n identity matrix); I wonder if there is a way to specify an
> > arbitrary covariance matrix.
> >
> > Thanks so much,
> >
> > Asaf
> >
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> >
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> >
>
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