nlmefit compound symmetry covariance pattern?

Hi, I am using nlmefit to fit a model of a "repeated measures" kind. The function provides very powerful control over the covariance matrix, but I could not find how to set compound symmetry. I have four measures, indicated in the design matrix as separate columns:

     X = [ measure==1  measure==2  measure==3  measure==4 ]

I would like the form

    [ x y y y
      y x y y 
      y y x y
      y y y x ]

Such that there is a fixed correlation between the four measures. But if I use

'covpattern', eye(4)+1

It doesn't constrain the `y` variances to be constant. When I examine `psi`, they are all free/estimated.

Answer 1

[the cyclist]

My understanding of the "CovPattern" input is that zero/nonzero entries merely indicate which terms can have covariance with each. For example, one of the documentation examples is

P =
     1     1     0
     1     1     0
     0     0     1

nlmefit(...,'CovPattern',P)

and the output covariance is

PSI =  
    0.5180    0.1069         0
    0.1069    0.0221         0
         0         0    0.0454

In your case, you put all nonzero entries -- the magnitudes are irrelevant, I think -- and you got covariance entries for all terms.

I don't know of a way to specify the covariance structure you want.