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Hi, I want to fit a GEE with a negative binomial distribution. I have uesd already a poisson glm and then neg binommial to deal with alot of dispersion. In my neg binomial residuals i have some patterns so i have implemented a GEE, but only with a poisson family as i couldnt with neg binomial. However the residual patterns in fact look worse here. When i try and put neg binomial family it

Hi, So I am trying to plot my results of a model. what i have is the majority of the data between the values of 0 and 30, then one outlier at 80 and another at 130. the model plots a nice line through the data between 0 to 30, however given the outliers you cant seen this unless you change the y axis using ylim=c(0,30) but then you can only see the data points in this range. What I would like

I am a new user, and i am trying to sort out a data frame. I have for example bins of data. Within each bin i have multiple counts of animals and the depths at which these count were taken. How would I summarise this to being only the maximum count per bin alongisde the corresponding height (but not the maximum depth - i want the depth at which the maximum number of animals occurs). Thank

Hi, I am trying to plot the original data with the line of the model using the predict function. I want to add SE to the graph, but not sure how to get them out as the predict function for gls does not appear to allow for SE=TRUE argument. Here is my code so far: f1<-formula(MaxNASC40_50~hu3+flcmax+TidalFlag) vf1Exp<-varExp(form=~hu3) B1D<-gls(f1,correlation=corGaus(form=Lat~Lon,