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 -- View this message in context: n4.nabble.com/nlme-w-no-groups-and-spatially-correlated-residuals-tp1477982p1477982.html Sent from the R help mailing list archive at Nabble.com.
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
Seemingly Similar Threads
- nlme and spatially correlated errors
- nonlinear (especially logistic) regression accounting for spatially correlated errors
- analyzing binomial data with spatially correlated errors
- how is xerror calculated in rpart?
- function to compare Brier scores from two models?