search for: waterbody_id

...any solution. I am running a generalised mixed effect model, gamm4, for an ecology project. Below is the code for the model: model<-gamm4(LIFE.OE_spring~s(Q95, by=super.end.group)+Year+Hms_Rsctned+Hms_Poaching+X.broadleaved_woodland? ? ? ? ? ? ?+X.urban.suburban+X.CapWks, data=spring, random=~(1|WATERBODY_ID/SITE_ID)) plot(model$gam, page=1, font.lab=2, xlab="Residual Q95") I am trying to plot the results in lattice for publication purposes so I need to figure this out. I have been struggling but I think I have reached a dead end.? Here is what I have been able to code: M<-predict(model$...

Hi Maria If you have problems just start with a small model with predictions and then plot with xyplot the same applies to xyplot Try library(gamm4) spring <- dget(file = "G:/1/example.txt") str(spring) 'data.frame': 11744 obs. of 11 variables: $ WATERBODY_ID : Factor w/ 1994 levels "GB102021072830",..: 1 1 2 2 2 3 3 3 4 4 ... $ SITE_ID : int 157166 157166 1636 1636 1636 1635 1635 1635 134261 1631 ... $ Year : int 2011 2014 2013 2006 2003 2002 2013 2005 2013 2006 ... $ Q95 : num 1...

...n the model to see the how the interaction term varies across the factor levels and get the plot for each factor in one page. Here is my code but I get the following message dat<-read.table("dat.txt", header=TRUE) str(dat) #'data.frame': 11744 obs. of 11 variables: #$ WATERBODY_ID : Factor w/ 1994 levels "GB102021072830",..: 1 1 2 2 2 3 3 3 4 4 5 5 5 5 5 6 ... #$ SITE_ID : int 157166 157166 1636 1636 1636 1635 1635 1635 134261 1631 65383 65383 65383 111828 ... #$ Year : int 2011 2014 2013 2006 2003 2002 2013 2005 2013 2006...