R help - Feb 2010 - nlme w/no groups and spatially correlated residuals

Hi,

I would like to specify a spherical correlation structure for spatially
autocorrelated residuals in a model based upon the logistic function of a
response that is a proportion (0 to 1) (so usual binary logistic regression
is not an option).  There is no need for a g-side random effect with
grouping in this model. Am I correct that nlme requires this (meaning a
correlated error structure only is not permissible)?  I have tried to
replicate the 'abuse' of the lme function I've seen for similar
problems
(specifying that all observations belong to one group), but this does not
seem to work for nlme.  Any legitimate work arounds?

Thanks,
Seth  
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Seth <sjmyers <at> syr.edu> writes:
> I would like to specify a spherical correlation structure for spatially
> autocorrelated residuals in a model based upon the logistic function of a
> response that is a proportion (0 to 1) (so usual binary logistic regression
> is not an option).  There is no need for a g-side random effect with
> grouping in this model. Am I correct that nlme requires this (meaning a
> correlated error structure only is not permissible)?  I have tried to
> replicate the 'abuse' of the lme function I've seen for similar
problems
> (specifying that all observations belong to one group), but this does not
> seem to work for nlme.  Any legitimate work arounds?
  The proportion part might be a bit tricky (you can only 
reasonably assume that the variation is normally distributed
if the variance is pretty small), but I think gnls() is what you're
looking for if you want non-linear least squares with correlation
and/or heteroscedasticity but without random effects.

  Ben Bolker