[R-sig-ME] Model with variable number of arguments

[Paul Johnson]

On Thu, Jul 30, 2015 at 8:34 AM, Daniel Kaschek
<daniel.kaschek at physik.uni-freiburg.de> wrote:
> Dear all,
>
> I have the following model:
>
> y_ij = x_i/s_j + (eps_ij)/s_j
>
> where y_ij are the responses, x_i and s_j are the fixed effects and the
> random effects follow a normal distribution
>
1.  x_i and s_j are observed variables or parameters you need to
estimate?  Why you have no betas?

2. the formulation using division is unfamiliar to me, but when you
get to this part

> eps_ij ~ N(0, sigma0^2 + x_i^2 * sigmaR^2)
>

Can't answer because I can't tell if x_i is observed or not.  If it is
not, I don't know that lme4 will help.

How did eps get this way in the first place.  It appears it might be
the sum of 2 separate random effects. If that's right, you are getting
closer to the sort of model I would understand

It makes me wonder why you don't have s_j inside the variance term
there,, or why you don't have both x_ and s_ outside.

Its pretty tough to read email with lots of x_i and such.  That part
is bad about plain text mailing lists

> with error parameters sigma0 and sigmaR. In the end, I am interested in
> the parameters x_i, s_j, sigma0 and sigmaR.
>
> First of all, is lme4 the right package to solve this problem? When
> looking at nlmer(), I had problems to figure out what would be the
> correct structure of the function in the middle of the 3-part-formula.
>
> Any help is appreciated.
>
> Thanks a lot in advance,
> Daniel
>
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-- 
Paul E. Johnson
Professor, Political Science        Director
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